How does economic performance differ across exchange rate regimes? Since theoretical predictions are varied and often conflicting, this section explores the question empirically for the period 1970 to 1999 using the Natural classification of de facto exchange rate regimes. This section offers an overarching conclusion while recognizing the limitations of such analyses—in particular, the possibility that economic performance influences the choice of regimes as much as regimes influence performance and that characterizing regimes is inherently difficult because a country’s unique history of regimes may be more relevant for economic outcomes than merely the ongoing regime. The findings suggest that exchange rate flexibility becomes more valuable as countries mature in terms of their access to international capital markets and as they develop sound financial systems. Below are three country groupings, each of which responds differently to exchange rate flexibility.
In developing countries, with their low exposure to international capital movements, relatively rigid regimes, such as pegs and intermediate flexibility arrangements, appear to have enhanced policy credibility and thus have helped achieve lower inflation at little apparent cost in terms of lost growth, higher growth volatility, or more frequent crises. The superior performance of pegged regimes required commitment, as shown through public announcement of that goal, and was further improved through consistent macroeconomic policies that allowed for longer regime duration.
In contrast, for emerging markets, with their higher exposure to international capital flows, the rigidity of regimes, particularly in the 1990s, was associated with more frequent banking crises and especially costly “twin” crises that included both financial sector and balance of payments turbulence. Moreover, rigid systems were not associated with obvious gains in terms of lower inflation or higher growth. At the same time, the move to full flexibility was inhibited by the concern that large swings in exchange rates could have adverse consequences. Case studies illustrate a variety of approaches to achieving greater flexibility.
In advanced countries, free floats registered faster growth than other regimes without incurring higher inflation. This benefit may reflect the typically more pronounced nominal rigidities in mature economies, giving flexible exchange rates an important role in reallocating resources following real shocks. Moreover, with financial maturity, widespread availability of debt denominated in domestic currency and in hedging instruments reduces the adverse consequences from currency mismatches that give rise to the fear of floating.
Though on average the value of exchange rate flexibility was found to increase with financial maturity, the results also suggest that the performance of any regime can be enhanced by consistent macroeconomic management. In particular, unified exchange rate systems have been associated with superior performance, and the declining trend of regimes with dual exchange rates that depart substantially from official rates (noted in Section II) is, therefore, a welcome one. Similarly, freely falling regimes, characterized by dysfunctional macroeconomic policies, have also been poor performers. The good news, once again, is that the incidence of freely falling regimes has declined steadily over the past decade. Furthermore, in developing and emerging economies the intermediate regimes—those lying between the two poles, or the two corners of pegs and free floats—have not fared systematically worse than the polar regimes, which is consistent with their longevity (also described in Section II).
The section is organized as follows. First, results of earlier empirical analysis are summarized, followed by a brief summary of the analytical issues to help interpret the results. Next, the study takes a first look at inflation, growth, growth volatility, and the incidence of crises across different exchange rate regimes, but does so without controlling for other factors that affect economic performance. It then controls for other determinants of economic performance and thus attempts to isolate the conditional relationship between exchange rate regimes and economic performance. Following is an assessment of whether the credibility underlying different exchange rate regimes can be enhanced through announcement of the regime and through policies that allow for longer regime duration, and includes case studies on how emerging markets can enhance their ability to effectively float their currencies. A recap concludes the section. An appendix summarizes the data and the econometric results discussed in this section.
Summary of Empirical Analysis of Exchange Rate Regimes
In guiding exchange rate regime choice, economic theory has proved to be an insufficient guide for policymakers. Empirical clarification is, thus, crucial. In part, theoretical ambiguity arises because the effects of particular regimes operate with varying strength in different economies. In empirical analysis, therefore, country types need to be distinguished, and this study contrasts the performance of regimes in developing economies, emerging markets, and advanced economies. Emerging markets, the subject of much of the recent policy discussion, differ from developing economies in terms of their higher exposure to international capital flows, but they continue nevertheless to exhibit important institutional and financial sector weakness. As a consequence, emerging markets face higher inflation, greater risk of debt unsustainability, more fragile financial systems, and higher propensity to macroeconomic volatility. Therefore, the emerging markets are characterized by more serious problems of credibility in the formulation of economic policy (see, for example, Fraga, Goldfajn, and Minella, 2003).
A more fundamental ambiguity arises in evaluating exchange rate regimes, where theoretical predictions lead to opposing conclusions. For example, while pegged regimes are generally thought to lower inflation, they may only postpone its manifestation. The growth effects of regimes depend on what is assumed about the shock-absorbing capacity of different regimes and how important these shock absorbers are in raising investment and productivity. Also, flexible exchange rates may dampen the volatility resulting from real external shocks, but this very flexibility may add to the volatility, with adverse economic consequences that lead to a fear of floating (Calvo and Reinhart, 2002).
Empirical analysis, however, has not delivered clear results either. In a well-known contribution, Baxter and Stockman (1989) compare the time-series behavior of key economic aggregates during and after the Bretton Woods system and finds that, aside from greater variability of real exchange rates under flexible systems, there is little difference in the behavior of key macroeconomic aggregates across different exchange rate arrangements. Mussa (1986) had reached similar conclusions earlier. Indeed, in their review of the literature up to that point, Edison and Melvin (1990) despair that the empirical effort to contrast economic performance across exchange rate regimes would ultimately prove inconclusive.
A recent generation of papers offers a more nuanced assessment. Using data for the post-Bretton Woods era for over 100 countries, the analysis initiated by Ghosh and others (1997) culminated in the comprehensive contribution of Ghosh, Guide, and Wolf (2003). These works deal with several empirically difficult issues. While they rely primarily on the de jure regime classification, they do make some effort to distinguish between the regime announced by national authorities and the one actually practiced. They also consider the perennially hard question of the direction of causality: do exchange rate regimes lead to particular macro outcomes or does performance determine the choice of regimes? Another important contribution is that by Levy-Yeyati and Sturzenegger (2002), who develop a different measure of de facto regimes (as discussed in Section II) and also attempts to deal with the causality issue.
The results of these studies, however, continue to conflict with each other, reflecting the differences in their methods of classifying regimes. Ghosh, Guide, and Wolf (2003) find that inflation under fixed exchange rate regimes is significantly lower than under intermediate or freely floating arrangements, due to greater confidence in the currency (a credibility effect) and lower money growth (a discipline effect), and that the benefit of pegged exchange rate regimes in terms of inflation performance is fairly robust to the endogeneity of regime choice. The study does not find evidence of a strong link between exchange rate regimes and economic growth, however, especially after controlling for country-specific effects and possible simultaneity bias. This result contrasts with Levy-Yeyati and Sturzenegger (2002), who use a de facto classification of regimes and finds for a similar sample that flexible exchange rates are associated with higher growth in developing countries—which includes the groups of countries referred to in this study as emerging markets. No similar association exists among industrial countries. Both Ghosh, Guide, and Wolf, and Levy-Yeyati and Sturzenegger find, however, that fixed exchange rate regimes are associated with somewhat higher output volatility.38
Against that background, this section reexamines the link between exchange rate regimes and economic performance along four dimensions: inflation, output growth, growth volatility, and the incidence of crises. The assessment is based on the recently constructed Natural classification, which identifies the prevailing de facto exchange rate regime as noted in Section II. The relative longevity of regimes under the Natural classification renders the reverse causality problem less serious than, for example, under the Levy-Yeyati-Sturzenegger classification, where regime classifications change as often as every year. Nevertheless, the section undertakes supplementary analysis to assess if the findings are robust to the reverse causality concern. Also, to allow for the possibility that the pressures under a particular regime are manifested after its collapse in a new regime, the section examines the lagged influence of regimes so that, in effect, the performance in the first year of a new regime continues to be attributed to the previous regime. This turns out to be important in the analysis of volatility in emerging markets. In addition, regime announcement and duration are considered as factors that may influence regime performance. The analysis covers up to 158 countries from 1970 to 1999, throughout which developing, emerging, and advanced economies are distinguished. Where appropriate, the 1990s, which was a period of rapidly rising capital flows, is distinguished from earlier years.
Analytical Considerations
An important prediction from economic theory is that exchange rate pegs act as a disciplining device, allowing policymakers in countries with a propensity for high inflation to import credibility and, hence, lower inflation from abroad (Giavazzi and Giovannini, 1989; and Dornbusch, 2001). As a policy prescription, nominal exchange rate rigidity—or an exchange rate anchor—came back into favor in the late 1980s and early 1990s, especially in Latin America, where exchange rate-based stabilizations were viewed as particularly helpful following a history of high inflation (Edwards, 2001). In this line of reasoning, the harder the peg, the more effective it is in enhancing credibility (Edwards and Magendzo, 2003a).
The proposition that pegs provide an inflation advantage is far from universally held, however. For advanced economies, pegged exchange rate regimes should not be necessary for achieving credibility. Even where such regimes could play a role, achieving and maintaining hard pegs is not a straightforward process. In particular, as exposure to international capital flows increases, a larger fraction of the monetary aggregates must be backed to maintain the peg. Hence, emerging markets are less likely to be able to import credibility than are other developing countries whose interaction with international capital markets is more limited. Tornell and Velasco (2000) raise the possibility that the inflationary gains from fixed regimes are illusory. No exchange rate system, the authors argue, can ultimately act as a substitute for sound macroeconomic policies. Far from exerting discipline, fixed exchange rate regimes may create an incentive for governments with short time horizons to cheat, delivering temporarily higher growth through larger deficits, with the full inflationary cost of such policies borne out following the eventual collapse of the peg.
The theoretical implications of exchange rate regimes for economic growth and volatility are similarly murky, with various opposing claims.39 In favor of pegs, Dornbusch (2001) argues that lower inflation associated with rigid exchange rate regimes would reduce interest rates and uncertainty, spurring investment and growth.40 Also, when a country ties its currency tightly to that of another through a currency board arrangement, transaction costs may be lowered, thereby increasing trade between the two countries. Frankel and Rose (2002) find that such expansion of trade is not offset by diversion away from other trade partners and that by increasing the openness of the economy this form of exchange rate rigidity also raises output growth. An argument in favor of exchange rate flexibility is the possibility of rapid resource reallocation following real shocks when short-run price rigidity is significant (Levy-Yeyati and Sturzenegger, 2003). Broda (2001) finds evidence that terms-of-trade shocks are amplified in countries that have more rigid exchange rate regimes. Edwards and Levy-Yeyati (2003) take that empirical analysis one step further and concludes that the inability of rigid regimes to absorb such shocks translates, in practice, into lower growth. Similarly, Calvo (1999) argues that the need to defend a peg following a negative external shock may result in high real interest rates and also stifle growth.
While flexible exchange rate regimes may, in principle, dampen real shocks to the economy, could the very flexibility of the exchange rate introduce a new element of volatility? As noted above, a robust finding is that nominal exchange rate volatility is associated with high real exchange rate volatility. Rogoff (1999) argues that such variability does not, in practice, have significant effects on output and consumption in advanced economies but may be harmful in developing countries. Even if the higher volatility has harmful effects, however, pegged regimes may not be the appropriate policy response because the volatility may only appear to be contained and may have real (adverse) effects on private investment due to the greater uncertainty over regime sustainability.
Indeed, just as the inflation-reducing benefits of exchange rate rigidity were being emphasized in the early 1990s, a fundamental reevaluation of the policy prescription was under way following the early crises associated with rigid regimes. For early recognition of this concern, see, for example, Eichengreen (1994), and Obstfeld and Rogoff (1995). The latter study notes that in 1995, following the collapse of the British pound in September 1992 and of the Mexican peso in December 1994, that “Many recent efforts to peg exchange rates within narrow ranges have ended in spectacular debacles.” The authors went on to conclude “These events are not unprecedented but their ferocity and scope have called into question the viability of fixed rates among sovereign nations in today’s world of highly developed global capital markets.” The subsequent fall of tightly managed regimes in East Asia (1997), Russia (1998), Brazil (1999), and Argentina (2002) have served as a continuing warning against pegged regimes, especially in emerging markets subject to volatile capital flows. Pegged exchange rates—or those with limited flexibility—invite speculative activity against the exchange rate and lead to abandonment of the peg, currency overshooting, and large output costs (Larraín and Velasco, 2001). Pegged regimes may also be subject to a higher incidence of banking crises. Under pegs, the exchange rate may become progressively overvalued, weakening the financial system; without, or with only limited, lender-of-last-resort capabilities, authorities may be unable to deal with domestic financial distress.
Table 3.1 summarizes these predictions for economic performance across regimes.
Economic Performance Across Exchange Rate Regimes
Economic Performance Across Exchange Rate Regimes
| Inflation | Growth | Volatility | Crisis | |
|---|---|---|---|---|
| Fixed | May enhance monetary policy credibility and lower inflation; emerging markets less likely to be able to import credibility; inflation, moreover, may be “bottled up” under weak macroeconomic management | May reduce transaction costs, and raise trade and growth; may also reduce interest rates and uncertainty, also raising investment and growth | May increase volatility in the presence of real shocks and nominal rigidities | High risk of speculative attacks against currency, especially when exposed to volatile capital flows; susceptibility to banking sector distress |
| Flexible | Declining importance of “imported” credibility with stronger institutions and financial sectors | Higher growth due to shock absorbers and fewer distortions following real shocks | Possible spilling over of real exchange rate volatility into real activity | Low risk of currency crises and banking crises |
Economic Performance Across Exchange Rate Regimes
| Inflation | Growth | Volatility | Crisis | |
|---|---|---|---|---|
| Fixed | May enhance monetary policy credibility and lower inflation; emerging markets less likely to be able to import credibility; inflation, moreover, may be “bottled up” under weak macroeconomic management | May reduce transaction costs, and raise trade and growth; may also reduce interest rates and uncertainty, also raising investment and growth | May increase volatility in the presence of real shocks and nominal rigidities | High risk of speculative attacks against currency, especially when exposed to volatile capital flows; susceptibility to banking sector distress |
| Flexible | Declining importance of “imported” credibility with stronger institutions and financial sectors | Higher growth due to shock absorbers and fewer distortions following real shocks | Possible spilling over of real exchange rate volatility into real activity | Low risk of currency crises and banking crises |
Macroeconomic Performance and Crisis Probabilities: Summary Statistics
Drawing on both the de facto and de jure classifications, the following portion describes the association between exchange rate regimes and various dimensions of economic performance. No attempt is made in this preliminary description to control for other factors that may also influence economic outcomes. First, a summary of average macroeconomic performance under alternate regimes is presented. Second, because the occurrence of crises has been particularly highlighted in recent policy discussions, the relationship between regimes and the frequency of banking and currency crises is documented.
Regimes and Performance: Summary Measures for Inflation, Growth, and Volatility
Conflicting policy objectives and large macroeconomic imbalances will lead to poor economic performance irrespective of the exchange rate regime. For the purposes of this discussion, there are at least two sets of conditions under which the exchange rate regimes may have no independent influence on macroeconomic outcomes through the prevailing severity of economic distortions. First, the prevalence of dual (or multiple) rates—and, hence, a potentially large differential in official and parallel market exchange rates—is a consideration in determining the operative regime as well as a factor influencing economic outcomes through the prevailing severity of economic distortions, as observed in Reinhart and Rogoff (2004). Second, the authors isolate countries with annual inflation rates above 40 percent into a separate freely falling category, with the implication that the macroeconomic imbalances in such conditions overwhelm the possible effects of the exchange rate regime.
The evidence suggests that dual exchange rates are associated with significantly worse economic performance. Over the period 1970–99, the average per capita income growth rate in countries with dual exchange rates was about 0.6 percent per year; in contrast, countries with unified rates grew at three times the pace, at about 1.8 percent per year (Table 3.2). Similarly, annual inflation in countries with dual exchange rates was about 175 percent, while under unified rates it was about 22 percent. These performance differences primarily reflect instances of large departures from official rates—the differences in median performance are less egregious. With increasingly integrated capital markets, large gaps between official and parallel rates have become untenable, and the move to unified exchange rates has been almost universal (see Section II).
Average Annual Inflation and Real Per Capita GDP Growth: Comparison of Dual (or Multiple) and Unified Exchange Rate Systems, 1970–991
(In percent)
Figures in parentheses are medians.
Average Annual Inflation and Real Per Capita GDP Growth: Comparison of Dual (or Multiple) and Unified Exchange Rate Systems, 1970–991
(In percent)
| Average Annual Inflation Rate | Average Per Capita GDP Growth | |
|---|---|---|
| Unified exchange rate | 22.0 | 1.8 |
| (7.7) | (2.1) | |
| Dual (or multiple) exchange rates | 175.6 | 0.6 |
| (15.1) | (1.4) |
Figures in parentheses are medians.
Average Annual Inflation and Real Per Capita GDP Growth: Comparison of Dual (or Multiple) and Unified Exchange Rate Systems, 1970–991
(In percent)
| Average Annual Inflation Rate | Average Per Capita GDP Growth | |
|---|---|---|
| Unified exchange rate | 22.0 | 1.8 |
| (7.7) | (2.1) | |
| Dual (or multiple) exchange rates | 175.6 | 0.6 |
| (15.1) | (1.4) |
Figures in parentheses are medians.
By their construction, freely falling regimes perform significantly worse than other regimes on all counts: they have higher inflation, lower growth rates, and higher volatility (Tables 3.3, 3.4, and 3.5). With the worldwide decline in inflation, the incidence of freely falling regimes is on the decline (Rogoff, 2003). For retrospective analyses, however, because freely falling episodes are typically classified under other systems as freely floating, their identification as a separate category in the Natural classification can make a significant difference to the relative rankings of regimes. For example, according to the de jure classification (the last column in Table 3.3), pegs have a much lower inflation rate than floating regimes. Under the Natural classification, however, freely floating regimes (the bottom row of Table 3.3) have, on average, lower inflation than exchange rate pegs. This reversal occurs because, as noted, many freely falling episodes are in the floating regime category according to the de jure classification. As noted below, when other influences on inflation are taken into account, the advantage of pegged and intermediate regimes over the floating regime reappears even in the Natural classification; however, not distinguishing the freely falling category renders that advantage much larger.
Average Annual Inflation Rates Across Exchange Rate Regimes, 1970–991
(In percent)
Figures in parentheses are medians.
Average Annual Inflation Rates Across Exchange Rate Regimes, 1970–991
(In percent)
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 17.9 | 9.6 | 14.2 | 24.5 | 391.7 | 12.4 | 33.9 |
| (6.8) | (7.9) | (10.4) | (23.2) | (39.9) | (6.5) | (7.9) | |
| Intermediate | 11.2 | 13.0 | 16.7 | 9.2 | 147.6 | 25.7 | 36.0 |
| (3.5) | (9.1) | (15.1) | (3.8) | (66.1) | (15.9) | (10.8) | |
| Floating | 20.3 | 10.1 | 11.3 | 8.1 | 408.9 | 445.6 | 138.5 |
| (11.5) | (7.5) | (8.4) | (4.5) | (68.6) | (22.2) | (10.8) | |
| Total | 17.1 | 11.1 | 14.2 | 9.9 | 305.3 | 55.5 | 49.7 |
| (6.5) | (8.3) | (10.8) | (4.8) | (57.0) | (7.6) | (8.7) |
Figures in parentheses are medians.
Average Annual Inflation Rates Across Exchange Rate Regimes, 1970–991
(In percent)
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 17.9 | 9.6 | 14.2 | 24.5 | 391.7 | 12.4 | 33.9 |
| (6.8) | (7.9) | (10.4) | (23.2) | (39.9) | (6.5) | (7.9) | |
| Intermediate | 11.2 | 13.0 | 16.7 | 9.2 | 147.6 | 25.7 | 36.0 |
| (3.5) | (9.1) | (15.1) | (3.8) | (66.1) | (15.9) | (10.8) | |
| Floating | 20.3 | 10.1 | 11.3 | 8.1 | 408.9 | 445.6 | 138.5 |
| (11.5) | (7.5) | (8.4) | (4.5) | (68.6) | (22.2) | (10.8) | |
| Total | 17.1 | 11.1 | 14.2 | 9.9 | 305.3 | 55.5 | 49.7 |
| (6.5) | (8.3) | (10.8) | (4.8) | (57.0) | (7.6) | (8.7) |
Figures in parentheses are medians.
Average Annual Real Per Capita GDP Growth Across Exchange Rate Regimes, 1970–991
(In percent)
Figures in parentheses are medians.
Average Annual Real Per Capita GDP Growth Across Exchange Rate Regimes, 1970–991
(In percent)
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 2.0 | 2.6 | 1.6 | –3.2 | –1.1 | 1.0 | 1.6 |
| (2.0) | (2.6) | (1.6) | (0.5) | (–0.7) | (0.6) | (1.6) | |
| Intermediate | 2.8 | 2.6 | 1.9 | 2.7 | 0.0 | 2.7 | 2.1 |
| (2.4) | (2.9) | (2.1) | (2.2) | (0.4) | (2.7) | (2.3) | |
| Floating | 3.6 | 1.7 | 1.6 | 2.2 | –3.1 | –1.6 | 0.6 |
| (2.9) | (1.8) | (2.2) | (2.3) | (–1.2) | (–0.3) | (1.7) | |
| Total | 2.1 | 2.4 | 1.7 | 1.8 | –1.3 | 0.8 | 1.5 |
| (2.2) | (2.6) | (2.0) | (2.0) | (–0.6) | (0.6) | (1.8) |
Figures in parentheses are medians.
Average Annual Real Per Capita GDP Growth Across Exchange Rate Regimes, 1970–991
(In percent)
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 2.0 | 2.6 | 1.6 | –3.2 | –1.1 | 1.0 | 1.6 |
| (2.0) | (2.6) | (1.6) | (0.5) | (–0.7) | (0.6) | (1.6) | |
| Intermediate | 2.8 | 2.6 | 1.9 | 2.7 | 0.0 | 2.7 | 2.1 |
| (2.4) | (2.9) | (2.1) | (2.2) | (0.4) | (2.7) | (2.3) | |
| Floating | 3.6 | 1.7 | 1.6 | 2.2 | –3.1 | –1.6 | 0.6 |
| (2.9) | (1.8) | (2.2) | (2.3) | (–1.2) | (–0.3) | (1.7) | |
| Total | 2.1 | 2.4 | 1.7 | 1.8 | –1.3 | 0.8 | 1.5 |
| (2.2) | (2.6) | (2.0) | (2.0) | (–0.6) | (0.6) | (1.8) |
Figures in parentheses are medians.
Average Annual Growth Volatility Across Exchange Rate Regimes, 1970–991
(In percent)
Figures in parentheses are medians.
Average Annual Growth Volatility Across Exchange Rate Regimes, 1970–991
(In percent)
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 4.0 | 3.8 | 3.6 | 5.7 | 4.3 | 4.3 | 4.0 |
| (2.7) | (2.3) | (2.6) | (3.3) | (3.4) | (2.9) | (2.7) | |
| Intermediate | 1.6 | 2.0 | 2.6 | 3.3 | 3.8 | 6.1 | 2.6 |
| (1.2) | (1.6) | (1.8) | (1.7) | (3.4) | (2.5) | (1.8) | |
| Floating | 3.1 | 2.4 | 4.1 | 1.9 | 6.4 | 4.9 | 3.8 |
| (1.8) | (1.5) | (1.9) | (1.1) | (4.6) | (2.9) | (1.9) | |
| Total | 3.7 | 2.8 | 3.5 | 2.7 | 4.7 | 4.5 | 3.7 |
| (2.4) | (1.8) | (2.3) | (1.3) | (3.7) | (2.9) | (2.4) |
Figures in parentheses are medians.
Average Annual Growth Volatility Across Exchange Rate Regimes, 1970–991
(In percent)
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 4.0 | 3.8 | 3.6 | 5.7 | 4.3 | 4.3 | 4.0 |
| (2.7) | (2.3) | (2.6) | (3.3) | (3.4) | (2.9) | (2.7) | |
| Intermediate | 1.6 | 2.0 | 2.6 | 3.3 | 3.8 | 6.1 | 2.6 |
| (1.2) | (1.6) | (1.8) | (1.7) | (3.4) | (2.5) | (1.8) | |
| Floating | 3.1 | 2.4 | 4.1 | 1.9 | 6.4 | 4.9 | 3.8 |
| (1.8) | (1.5) | (1.9) | (1.1) | (4.6) | (2.9) | (1.9) | |
| Total | 3.7 | 2.8 | 3.5 | 2.7 | 4.7 | 4.5 | 3.7 |
| (2.4) | (1.8) | (2.3) | (1.3) | (3.7) | (2.9) | (2.4) |
Figures in parentheses are medians.
The performance of intermediate regimes is not especially different from that of other regimes (Tables 3.3, 3.4, and 3.5). This is consistent with the longevity of these regimes, as documented in Section II. If this comparison had revealed consistently poorer performance under intermediate regimes, there would have been a greater basis for expecting a shift to the polar extremes of pegs and free floats.
Finally, as documented by Mussa (1986), Baxter and Stockman (1989), and Flood and Rose (1995), real exchange rates are more variable the greater the flexibility of the regime (Table 3.6). Exchange rate volatility is considerably higher under managed floating and freely floating regimes than under pegged and limited flexibility regimes. This reflects the fact that real rates tend, at least in the short run, to move closely with nominal rates. Notably, more flexibility under the de jure classification is not associated with greater variability of the real exchange rate because regimes that are declared flexible are often tightly managed.
Real Exchange Rate Volatility Across Exchange Rate Regimes, 1970–20021
Volatility is measured as the three-year centered standard deviation of the annual real effective exchange rate (IFS, line RECZF). Nicaragua is excluded from this table because its exchange rate has been extremely volatile, and its inclusion unduly influences the averages.
Real Exchange Rate Volatility Across Exchange Rate Regimes, 1970–20021
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 6.3 | 8.9 | 25.1 | 7.0 | 53.6 | 6.6 | 12.7 |
| Intermediate | 3.2 | 4.8 | 10.5 | 30.6 | 42.3 | 28.4 | 12.1 |
| Floating | 10.5 | 5.2 | 11.6 | 8.4 | 17.3 | 14.8 | 10.4 |
| Total | 5.6 | 6.1 | 17.9 | 13.7 | 37.0 | 9.2 | 12.0 |
Volatility is measured as the three-year centered standard deviation of the annual real effective exchange rate (IFS, line RECZF). Nicaragua is excluded from this table because its exchange rate has been extremely volatile, and its inclusion unduly influences the averages.
Real Exchange Rate Volatility Across Exchange Rate Regimes, 1970–20021
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Freely Falling | Unknown | Total | |
|---|---|---|---|---|---|---|---|
| Pegged | 6.3 | 8.9 | 25.1 | 7.0 | 53.6 | 6.6 | 12.7 |
| Intermediate | 3.2 | 4.8 | 10.5 | 30.6 | 42.3 | 28.4 | 12.1 |
| Floating | 10.5 | 5.2 | 11.6 | 8.4 | 17.3 | 14.8 | 10.4 |
| Total | 5.6 | 6.1 | 17.9 | 13.7 | 37.0 | 9.2 | 12.0 |
Volatility is measured as the three-year centered standard deviation of the annual real effective exchange rate (IFS, line RECZF). Nicaragua is excluded from this table because its exchange rate has been extremely volatile, and its inclusion unduly influences the averages.
Regimes and Crisis Probabilities
In the 1990s, several economies with rigid exchange rate regimes were victims of severe economic crises. A concern thus arose not just for the prospects of the economies directly subject to the crises but also for the possible contagion of crises across countries with similar economic features following a general loss of investor confidence. The occurrence of crises has, therefore, acquired greater prominence in the policy discussions on the choice of exchange rate regimes. Despite the policy interest, few systematic studies have examined the links between crises and exchange rate regimes.
The evidence presented in this section suggests that popular perception in this regard has some statistical basis. While the evidence on currency crises is mixed, the frequency of banking and twin crises, where banking and currency turbulence come together, has been higher under more rigid regimes but mainly for emerging markets, and particularly so in the 1990s. As noted in the introduction, emerging markets are more exposed to international capital flows than are other developing economies, but compared to advanced industrialized economies emerging markets have fragile financial sectors.41
Consider, first, the frequency of banking crises.42 More rigid regimes had a higher likelihood of banking crises, especially in the 1990s. For all countries, during the period 1980–97, the probability of a banking crisis in a given year varied between about 3 and 4.5 percent, with no clear variation across exchange rate regimes (Table 3.7).43 The highest probabilities of a banking crisis occurred in the emerging market economies, however, where the evidence also suggests that the probability of a crisis increased with the rigidity of the exchange rate regime. Moreover, the association between rigidity and probability of banking crises in emerging markets became stronger in the 1990s.
Probability of Crises During Specific Regimes Using the Natural Exchange Rate Regime Classification1
(In percent)
Probabilities are calculated by dividing the number of occurrences of a crisis under a particular regime by the total number of regime years. Each crisis is counted only once, and hence, if it persists over multiple years, the subsequent years are not taken into account for this calculation. Additionally, the years an exchange rate regime transition takes place (i.e., the year preceding, the year during, and the year following the transition) are excluded from this computation. A dash (—) indicates that no crisis data were available for developing countries under freely floating exchange rate regimes.
Probability of Crises During Specific Regimes Using the Natural Exchange Rate Regime Classification1
(In percent)
| Bank Crisis (1980–97) | Bank Crisis (1990–97) | ||||||||
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Peg | Limited Flexibility | Managed Floating | Freely Floating | ||
| All | 3.4 | 4.7 | 4.5 | 3.9 | 3.1 | 7.1 | 3.0 | 3.8 | |
| Advanced | 0.0 | 2.7 | 2.3 | 4.1 | 0.0 | 6.5 | 0.0 | 4.2 | |
| Emerging | 11.4 | 7.5 | 7.0 | 0.0 | 15.4 | 8.0 | 3.8 | 0.0 | |
| Developing | 2.8 | 7.0 | 3.6 | — | 2.6 | 7.1 | 4.5 | — | |
| Balance of Payments Crisis (1970–2000) | Balance of Payments Crisis (1990–2000) | ||||||||
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Peg | Limited Flexibility | Managed Floating | Freely Floating | ||
| All | 4.1 | 4.1 | 9.2 | 4.6 | 4.7 | 5.2 | 9.2 | 4.3 | |
| Advanced | 3.3 | 3.9 | 7.1 | 4.9 | 3.6 | 5.8 | 8.6 | 4.9 | |
| Emerging | 4.6 | 5.6 | 10.0 | 0.0 | 8.8 | 6.1 | 6.9 | 0.0 | |
| Developing | 5.2 | 2.0 | 9.7 | — | 0.0 | 2.8 | 15.4 | — | |
| Twin Crises (1980–97) | Twin Crises (1990–97) | ||||||||
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Peg | Limited Flexibility | Managed Floating | Freely Floating | ||
| All | 1.6 | 1.4 | 0.8 | 0.0 | 3.2 | 2.6 | 0.0 | 0.0 | |
| Advanced | 0.0 | 0.7 | 0.0 | 0.0 | 0.0 | 2.2 | 0.0 | 0.0 | |
| Emerging | 7.7 | 3.0 | 1.8 | 0.0 | 15.4 | 4.0 | 0.0 | 0.0 | |
| Developing | 0.0 | 0.0 | 0.0 | — | 0.0 | 0.0 | 0.0 | — | |
Probabilities are calculated by dividing the number of occurrences of a crisis under a particular regime by the total number of regime years. Each crisis is counted only once, and hence, if it persists over multiple years, the subsequent years are not taken into account for this calculation. Additionally, the years an exchange rate regime transition takes place (i.e., the year preceding, the year during, and the year following the transition) are excluded from this computation. A dash (—) indicates that no crisis data were available for developing countries under freely floating exchange rate regimes.
Probability of Crises During Specific Regimes Using the Natural Exchange Rate Regime Classification1
(In percent)
| Bank Crisis (1980–97) | Bank Crisis (1990–97) | ||||||||
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Peg | Limited Flexibility | Managed Floating | Freely Floating | ||
| All | 3.4 | 4.7 | 4.5 | 3.9 | 3.1 | 7.1 | 3.0 | 3.8 | |
| Advanced | 0.0 | 2.7 | 2.3 | 4.1 | 0.0 | 6.5 | 0.0 | 4.2 | |
| Emerging | 11.4 | 7.5 | 7.0 | 0.0 | 15.4 | 8.0 | 3.8 | 0.0 | |
| Developing | 2.8 | 7.0 | 3.6 | — | 2.6 | 7.1 | 4.5 | — | |
| Balance of Payments Crisis (1970–2000) | Balance of Payments Crisis (1990–2000) | ||||||||
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Peg | Limited Flexibility | Managed Floating | Freely Floating | ||
| All | 4.1 | 4.1 | 9.2 | 4.6 | 4.7 | 5.2 | 9.2 | 4.3 | |
| Advanced | 3.3 | 3.9 | 7.1 | 4.9 | 3.6 | 5.8 | 8.6 | 4.9 | |
| Emerging | 4.6 | 5.6 | 10.0 | 0.0 | 8.8 | 6.1 | 6.9 | 0.0 | |
| Developing | 5.2 | 2.0 | 9.7 | — | 0.0 | 2.8 | 15.4 | — | |
| Twin Crises (1980–97) | Twin Crises (1990–97) | ||||||||
| Peg | Limited Flexibility | Managed Floating | Freely Floating | Peg | Limited Flexibility | Managed Floating | Freely Floating | ||
| All | 1.6 | 1.4 | 0.8 | 0.0 | 3.2 | 2.6 | 0.0 | 0.0 | |
| Advanced | 0.0 | 0.7 | 0.0 | 0.0 | 0.0 | 2.2 | 0.0 | 0.0 | |
| Emerging | 7.7 | 3.0 | 1.8 | 0.0 | 15.4 | 4.0 | 0.0 | 0.0 | |
| Developing | 0.0 | 0.0 | 0.0 | — | 0.0 | 0.0 | 0.0 | — | |
Probabilities are calculated by dividing the number of occurrences of a crisis under a particular regime by the total number of regime years. Each crisis is counted only once, and hence, if it persists over multiple years, the subsequent years are not taken into account for this calculation. Additionally, the years an exchange rate regime transition takes place (i.e., the year preceding, the year during, and the year following the transition) are excluded from this computation. A dash (—) indicates that no crisis data were available for developing countries under freely floating exchange rate regimes.
The finding that banking crises are more likely to occur under rigid regimes is in contrast to that of Ghosh, Guide, and Wolf (2003), who conclude that, if anything, floating regimes are the most likely to experience banking crises. The difference in findings is the consequence of the latter’s use of the de jure classification, which has many more countries classified as floating than does the Natural classification. As noted in Section II, many of these de jure floaters are classified under the Natural classification as freely falling; other floaters did not actually float and so were de facto under more rigid regime categories. As a consequence, using the de jure classification leads to an overstatement of the likelihood of banking crises under floating regimes and an understatement of crisis probabilities under more rigid regimes.
Currency crises over the years 1970 to 2000 tended to occur more frequently in intermediate regimes, based on a measure of currency crises employed by Berg, Borensztein, and Pattillo (2004).44 The evidence for the 1990s is less clear cut and suggests that, among emerging markets, pegged regimes had more frequent currency crises. An alternative measure of currency crises, using different thresholds for exchange rate depreciation and loss in reserves (Bordo and others, 2001), shows that pegs and limited flexibility had a significantly higher risk of currency crisis than managed or freely floating regimes45 for emerging markets.
Finally, twin crises have been almost uniquely an emerging market phenomenon: they have never occurred in the group of countries classified as developing and rarely in advanced economies. Moreover, the incidence of twin crises in emerging markets is highest under pegged regimes and falls as flexibility in regimes increases. Kaminsky and Reinhart (1999) have noted that twin crises have particularly high costs. Such crises typically start with domestic financial distress, which accelerates when a currency crisis also sets in, leading to a vicious cycle. Costs are high in terms of bailout of the financial sector as well as in terms of reserves lost. Larraín and Velasco (2001) provide a theoretical discussion of why currency boards may be particularly prone to twin crises. Rigid regimes may promote excessive risk taking during periods of booms in capital inflows, when the expectation of an exchange rate guarantee reduces the incentive to hedge foreign currency exposure. The sudden withdrawal of flows leaves the domestic financial sector susceptible to severe distress. At the same time, the commitment to an exchange rate target limits lender-of-last-resort operations. If depositors withdraw domestic currency from domestic banks to buy the foreign reserve currency at the central bank under a fixed exchange rate, the panic withdrawal can lead to a self-fulfilling crisis as foreign currency reserves are depleted. Argentina’s massive collapse is a cautionary tale of how some of these forces can contribute to the unraveling of even a hard peg.
Regime Performance and Levels of Development
While the previous section reported correlations, this section takes the more demanding step of attempting to isolate, over the period 1970–99, the association between exchange rate regimes and the performance measures of interest, after controlling for other variables that may also influence performance.46 But even after such controls are included, reverse causality, or endogeneity, remains a concern in such analyses: in other words, the observed relationships may reflect the influence of the performance variable on the choice of the regime rather than the other way around. This problem cannot be fully resolved, but it is mitigated by the relatively long duration of the typical regime under the Natural classification, implying that temporary changes in performance do not influence the choice of regime. The problem is also mitigated by using as an explanatory variable the regime prevailing in the previous one or two years where the results presented are unchanged when that is done, except, as discussed below, in the analysis of volatility in emerging markets.47
Inflation Performance Across Exchange Rate Regimes
A wide range of empirical studies have found that fixed exchange rate regimes deliver lower inflation. IMF (1997) found that the median inflation rates for fixed regimes have been lower than those for floating regimes, though the difference declined over time. More rigorous studies that control for other determinants of inflation—for example, Ghosh, Guide, and Wolf (2003) and Edwards and Magendzo (2003a and 2003b)—support this conclusion. It turns out, however, to be important to distinguish between different country types. On average, pegged and intermediate regimes have been associated with significantly lower inflation rates than floating regimes, but this reflects an inflation benefit that accrues primarily to developing economies and not to emerging markets or advanced economies.48
Before examining the differentiation across country groups, it is useful to note that the findings with respect to inflation performance across all countries are similar whether the de jure or the Natural classification is used. Figure 3.1, which pools all countries, contrasts the results using the de jure classification with those for the Natural classification. The bars in the figure represent the difference in inflation in intermediate and floating rate regimes relative to pegged regimes, after controlling for a variety of factors thought to influence inflation in all regimes.49 Because the regressions control for money growth, they can be thought of as capturing the value of credibility rather than greater discipline, whereby pegs generate lower inflation through control on the growth of money supply, for example. Using the de jure classification, floating regimes are associated with significantly higher inflation than pegged regimes, on average 6.2 percent.
Inflation Performance Across Regimes: Confidence Effect 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Inflation Performance Across Regimes: Confidence Effect 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Inflation Performance Across Regimes: Confidence Effect 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.For the Natural classification, pegged regimes continue to exhibit significantly lower inflation than freely floating regimes, though the margin by which they do so (4.5 percent) is smaller. In addition, intermediate regimes now perform significantly better (by 2.9 percent) than floating regimes in terms of inflation. Separating out the freely falling category reduces the average inflation rate for freely floating regimes, thereby reducing the inflation advantage of pegged regimes and giving some inflation advantage to intermediate regimes.
The effect on inflation through potentially greater monetary discipline under restrictive regimes is significantly smaller than that due to enhanced credibility. Figure 3.2 captures the discipline effect by attributing differences in rates of money supply growth to the regimes themselves and thus imputing additional discipline effects based on these differences. Using the de jure classification, the discipline effect adds to the inflation advantage of pegged regimes somewhat. The same holds for the Natural classification, where the inflation advantage attributed to exchange rate pegs and to intermediate regimes relative to floating rises modestly. But overall these effects are small.
Inflation Performance Across Regimes: Confidence and Discipline Effects 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Inflation Performance Across Regimes: Confidence and Discipline Effects 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Inflation Performance Across Regimes: Confidence and Discipline Effects 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.A different story emerges when inflation performance is distinguished across the advanced countries group, emerging markets, and developing countries (Figures 3.3 and 3.4). In developing countries, inflation performance deteriorates with exchange rate flexibility. The results indicate that pegged regimes have the lowest inflation, about 2.5 percent per annum lower than countries with intermediate flexibility; floating regimes experience inflation that is about 8 percent a year more than regimes with intermediate flexibility. Note that, though the difference between pegs and intermediate regimes is not statistically significant, the difference between pegs and floating regimes is highly significant. This result holds up consistently in a variety of empirical specifications (see, for example, Table A3.4 in the appendix).
Inflation Performance in Advanced Countries, Emerging Markets, and Deveioping Countries: Confidence Effect 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Inflation Performance in Advanced Countries, Emerging Markets, and Deveioping Countries: Confidence Effect 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Inflation Performance in Advanced Countries, Emerging Markets, and Deveioping Countries: Confidence Effect 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Inflation Performance in Advanced Countries, Emerging Markets, and Developing Countries: Confidence and Discipline Effects 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Inflation Performance in Advanced Countries, Emerging Markets, and Developing Countries: Confidence and Discipline Effects 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Inflation Performance in Advanced Countries, Emerging Markets, and Developing Countries: Confidence and Discipline Effects 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.In emerging markets, inflation performance shows no significant relationship with greater exchange rate flexibility. When, however, the regime prevailing in the prior one or two years is used as the explanatory variable (to minimize the influence of the relatively high rate of regime transitions in this group of countries), there is some evidence that, as in developing economies, inflation rises with flexibility. This may explain the fear of floating50 because the reduction in pass-through to domestic prices may take time. For advanced countries, there is evidence that inflation actually declines with increased exchange rate flexibility. While the direction of the results typically favors floating over pegged, the results in alternate specifications are not always so clear, and the appropriate conclusion appears to be that floating regimes do no worse than pegged regimes in terms of inflation performance in advanced economies. These differences across advanced countries, emerging markets, and developing countries are similarly apparent in Figure 3.4, which incorporates the above-mentioned discipline effects via monetary policy.
Overall, these results suggest that there may be some merit to pegged and intermediate regimes in developing countries perhaps reflecting the fact that, in the absence of sound institutions and a strong track record, these regimes can enhance policy credibility and discipline monetary policy. This does not, of course, imply a blanket recommendation of pegged regimes because many country-specific features would need to be taken into account in making that decision, including the appropriate level at which to peg the exchange rate. As countries gain access to international capital markets, there appears to be no evidence of inflation reduction through the adoption of rigid regimes.
Per Capita Income Growth Across Exchange Rate Regimes
Does the inflation advantage of pegged and intermediate over floating regimes in developing countries help growth (through reduced interest rates and lower uncertainty, as Dornbusch, 2001, suggests); does it come at the expense of growth; or does the exchange rate regime make no difference to growth (as Eichengreen, 2001, concludes)?
For the full sample of countries (Figure 3.5), both the de jure and de facto classifications show virtually no relationship between exchange rate flexibility and growth.51 For developing economies (Figure 3.6), growth appears to decline with increased flexibility, though the effect is not statistically significant. Thus, the association observed above of lower inflation with greater rigidity apparently does not come at the expense of growth; but neither does lower inflation have a measurable favorable effect through, for example, lower interest rates and reduced uncertainty. For emerging markets, the relationship between growth and regimes is noisy, as with inflation.
Growth Performance Across Regimes 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Growth Performance Across Regimes 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Growth Performance Across Regimes 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Growth Performance in Advanced Countries, Emerging Markets, and Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Growth Performance in Advanced Countries, Emerging Markets, and Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Growth Performance in Advanced Countries, Emerging Markets, and Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.In contrast, for advanced countries free floats do significantly better than other regimes in terms of growth performance. Indeed, the results suggest that for advanced economies exchange rate rigidity is monotonically associated with slower growth, which is even more apparent when regimes are lagged, as reported in the appendix. Because in the advanced countries no inflation benefit is associated with greater rigidity—indeed, if anything, inflation performance worsens with more regime rigidity—there appears to be an overall benefit from floating.52
The beneficial influence of flexible regimes as countries become more advanced is consistent with the view that floating permits more rapid adjustment following shocks, and that with stronger institutions—in particular, deep financial sectors—advanced economies are not subject to the offsetting risks of floating. Bordo and Flandreau (2001), in line with Calvo and Reinhart (2002), note that where domestic financial markets are underdeveloped, borrowing in foreign currency creates significant risks of sharp changes in an enterprise’s net worth when exchange rates are flexible. As borrowing in domestic currencies becomes a viable option, the costs of flexibility fall.53 Bordo (2003) makes the further argument that advanced economies have always been more successful in managing the trade-off between achieving credibility and retaining flexibility. The author suggests that even during the period of the classical gold standard when exchange rates were fixed, the margin permitted by gold points allowed temporary changes in exchange rates. Of importance is the observation that these exchange rate changes were expected to be temporary—to deal with shocks—and hence a reversion to the parity was expected. In contrast, where credibility is low, deviations can generate the expectation of further deviations.
Growth Volatility Across Exchange Rate Regimes
Finally, consider the relationship between exchange rate regimes and output growth volatility.54 When using the Natural classification, growth volatility does not appear to vary systematically across regimes and across all countries (Figure 3.7).55 However, while there is essentially no relationship for developing countries, volatility appears to increase with flexibility in the other two groups of countries (Figure 3.8). The increase in volatility with flexibility in advanced economies comes at apparently little or no cost, as Rogoff (1999) suggests, and as implied by the earlier findings that flexibility is associated with higher growth and lower inflation.
Volatility of Real GDP Growth Performance Across Regimes 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Volatility of Real GDP Growth Performance Across Regimes 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Volatility of Real GDP Growth Performance Across Regimes 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Volatility of Real GDP Growth Performance in Advanced Countries, Emerging Markets, and Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Volatility of Real GDP Growth Performance in Advanced Countries, Emerging Markets, and Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Volatility of Real GDP Growth Performance in Advanced Countries, Emerging Markets, and Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.For emerging markets, the story is more complex (Figure 3.8). Here there appears at first to be higher volatility associated with more flexibility. Two considerations, however, caution against that conclusion. First, the volatility associated with the collapse of rigid regimes is likely to register during subsequent regimes—an important consideration for emerging markets with their relatively high rate of transitions. Figure 3.9 investigates whether this phenomenon is quantitatively important. It compares the estimated volatility effects of regimes that prevailed in the previous one and two years (on the assumption that the spillover effects will be manifested mainly in the first two years of transition to a new regime). Now, the volatility in pegged regimes is actually higher relative to limited flexibility and freely floating, with little difference relative to managed floating. These results are not all statistically significant, but they point to significant spillover effects when transitions from pegged regimes occur. The implication is that the apparent relationship in emerging markets between flexibility and higher volatility is due largely to the volatility following the collapse of rigid regimes being attributed to subsequent more flexible regimes. Second, the transmission of volatility from rigid to flexible regimes appears more so the case for the 1990s, when the countries identified here as emerging markets began to tap international capital in a significant manner (Figure 3.10). Together with their higher likelihood of twin crises, as reported above, this appears to further strengthen the case against rigid regimes for emerging markets.
Volatility of Real GDP Growth and Contamination Across Regimes: Evidence from Emerging Markets 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Volatility of Real GDP Growth and Contamination Across Regimes: Evidence from Emerging Markets 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Volatility of Real GDP Growth and Contamination Across Regimes: Evidence from Emerging Markets 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Volatility of Real GDP Growth Across Regimes: Emerging Markets for the 1990s Only 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
Volatility of Real GDP Growth Across Regimes: Emerging Markets for the 1990s Only 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Volatility of Real GDP Growth Across Regimes: Emerging Markets for the 1990s Only 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Achieving Credibility in Developing and Emerging Economies
The results given above suggest that for developing economies a benefit in the form of lower inflation has been associated with pegged and intermediate regimes and that such a benefit has not come at the expense of lower growth or higher volatility. Moreover, the inflation benefit of these relatively rigid regimes was found to accrue primarily through a credibility effect rather than through greater monetary discipline. Following is an investigation as to how developing countries can further enhance the credibility of their exchange rate regimes to improve macroeconomic performance. With respect to emerging markets, which do not seem to derive appreciable benefits from rigid regimes but also fear to float, the performance of floating regimes and whether they can be improved is examined below.
Announcement Effects
Is there an incremental inflation benefit associated with officially announcing an operative pegged regime? The presumption is that announcement implies a stronger commitment to maintaining the peg and hence to policies that are supportive of that regime. To consider the announcement effect, the overlap between de facto and de jure regimes was identified. The statistical task was to determine if the overlap added value to the regime.
Among developing countries, this announcement effect is large and significant for pegged regimes. As Figure 3.11 shows, once a separate announcement effect is allowed for, the small number of developing countries that pursued exchange rate pegs without explicitly announcing that policy exhibited average inflation that, if anything, was somewhat higher than that in other (especially intermediate) regimes. In other words, the inflation benefit of pegged regimes identified above did not derive merely from operating a tightly managed exchange rate. The big gain came only when the peg was official. In Figure 3.11 it is also interesting to note that the announcement of other regimes had the opposite effect of raising inflation. Thus the announcement benefit differentiated pegs from other regimes in an important way.
The Inflation Benefit Associated with Announcement in Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.
The Inflation Benefit Associated with Announcement in Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.The Inflation Benefit Associated with Announcement in Developing Countries 1
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.Regime Duration
Regimes that last longer presumably do so because macroeconomic policies are maintained in a consistent manner over time. If so, longer duration should add to a regime’s credibility and be associated with superior performance. To proxy for the consistency of the macroeconomic stance with respect to the exchange rate regime, its duration (the number of years that a particular regime has been in force) was treated as an additional dimension of its characteristics.
The results imply that in developing countries pegged regimes delivered an inflation benefit even with no track record (i.e., with zero duration). In addition, the duration dimension for pegged regimes was highly significant and negative (-0.2 percent per year). Additionally, the calculations show that countries that maintained pegged regimes over a period of 10 years, for example, may have earned an additional inflation benefit of more than 80 percent over the initial inflation gain (see Figure 3.12).
The Inflation Benefit Associated with Consistent Macroeconomic Policies in Developing Countries1,2
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.2 Measured as the additional inflation benefit from maintaining a given regime for 10 years.
The Inflation Benefit Associated with Consistent Macroeconomic Policies in Developing Countries1,2
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.2 Measured as the additional inflation benefit from maintaining a given regime for 10 years.The Inflation Benefit Associated with Consistent Macroeconomic Policies in Developing Countries1,2
(In percent)
Source: Authors’ calculations.1 Figures in parentheses are t-statistics. The bars depict differences in performance relative to pegged exchange rate regimes, conditioning on a range of other variables. See appendix in Section III for details.2 Measured as the additional inflation benefit from maintaining a given regime for 10 years.Taken together, the lesson appears to be that developing countries that announce their peg and are able to maintain them over longer durations derive greater benefits from the rigidity in exchange rate regimes. While this finding is prima facie encouraging, it may be an insufficient policy guide in the context of the growing importance of international capital flows. Obstfeld and Rogoff (1995) note that most countries with long-lasting pegs adopted them in times when global capital markets were relatively shallow. Having achieved credibility during that less-demanding period, they were often able to maintain the pegs even with greater exposure to international capital. Those countries seeking to establish credibility in the current context, however, are likely to find that a more challenging task.
Learning to Float
What does the future hold for emerging markets, particularly middle-income, open-capital account countries? These rigid regimes run the risk of triggering crises, and concerns arising from large movements or excessive volatility of the exchange rate limit the extent of flexibility that policymakers are willing to allow. These countries currently manage their exchange rates to varying degrees while pursuing domestic monetary policies—increasingly some variant of inflation targeting—to anchor inflationary expectations. The finding reported earlier that floating becomes a superior alternative as institutional capabilities become stronger raises the possibility that the more developed emerging market economies may wish to anticipate a further move to floating and hence begin to invest in learning to float.
Opposing views exist on the feasibility of learning to float. One fairly pessimistic view (Eichengreen, Hausmann, and Panizza, 2004) hold that the risk of a sharp depreciation under floating rates will depress investment activity in most emerging markets because (unhedged) foreign currency borrowing will always be significant. This handicap, the authors argue, cannot be overcome without coordinated international action to facilitate countries’ borrowing in their own currency. As a result, floating exchange rates, in this view, will remain mostly a mirage.
Another perspective starts by noting that floating is relatively new, and the experience with it thus far has been fairly positive (Edwards and Savastano, 1999; and Larraín and Velasco, 2001). While in practice emerging market floaters are far from pure, in that intervention is common and the authorities generally take the exchange rate directly into account in setting monetary policy, there has been meaningful and in some ways effective floating. Inflation objectives have been met and countercyclical policy has been possible. Goldstein (2002) summarizes the available evidence as suggesting that emerging markets can conduct floating in combination with inflation-targeting monetary policy and measures to discourage currency mismatch in a way that credibly achieves low inflation; buffers external shocks, such as to the terms-of-trade; and provides some independence of monetary policy. Ho and McCauley (2003) argue, in their review of recent experience that where exchange rate considerations have been opposed to inflation targets, inflation has typically been the primary objective of policy.56
There is reason to believe emerging market economies can improve the flexibility and effectiveness of their floats over time. Such learning to float could take place through two main channels. The first is through the acquisition of confidence and experience on the part of the authorities. The authorities themselves need to learn how to conduct monetary policy appropriate to a flexible exchange rate. It may take time, for example, for the central bank to refine the new internal procedures and communication strategies involved in inflation targeting. Moreover, the authorities may need time and experience to build trust in their own framework and to become comfortable with allowing substantial exchange rate flexibility. The second is through modified behavior on the part of private agents, who may adjust their behavior as they observe flexible exchange rates in action and come to appreciate the risks involved in unhedged foreign exchange positions. This adjustment in behavior would, in turn, reduce banking system dollarization as lenders and borrowers appreciate and price the risks involved in currency mismatch (Ize and Levy-Yeyati, 2003). Similarly, expectations that the central bank will in fact allow exchange rate flexibility may diminish incentives to accept excessive foreign currency-denominated capital inflows (Caballero and Krishnamurthy, 2002). Finally, as private agents observe that the authorities can keep inflation low in the context of a floating exchange rate regime, their inflation expectations may respond less to movements in the exchange rate, thus reducing the pass-through from exchange rates to inflation. The dynamics associated with learning to float would allow a sort of virtuous circle, at least for those countries that can demonstrate some initial effectiveness in floating.57
The experience of at least three emerging market floaters may be consistent with this dynamic. Consider the case of Chile, which in the late 1990s tran-sited from a framework with both an inflation target and an explicit exchange rate band to a more pure form of floating. Chile went through two episodes of exchange rate pressure, in late 1998 and late 2000. In the first episode, associated with the Russian and long-term capital management crises, interest rates increased sharply as the authorities defended the exchange rate within the band. Thus, the weakening exchange rate was accompanied by a sharp interest rate increase, as well as a sharp recession. In the second episode of exchange market pressure, in late 2000, the authorities allowed the currency to float, in line with the new exchange rate arrangement introduced in August 1999, according to which the exchange band was discontinued and intervention was limited to extreme circumstances.
Mexico is another country that has seen inflation come down in the context of a regime that has also become gradually more flexible. Once the immediate postcrisis period was over in 1995, the authorities paid substantial attention to the exchange rate in the conduct of their monetary policy. Over time, they adopted more formal inflation targeting and allowed substantial movements in the real exchange rate. Inflation and both nominal and real interest rates have come down fairly steadily. Inflation persistence has declined over time, suggesting perhaps an increasing credibility of the monetary authorities.58 At the same time, Martínez and Werner (2002) conclude that the exposure of Mexican firms to devaluation risk has lessened with the flexible exchange rate regime in place since the 1994/1995 crisis.
Finally, Brazil is a third country that has been floating its exchange rate while at the same time building a track record of low and stable inflationary expectations through inflation targeting. Fraga, Goldfajn, and Minella (2003) describe the challenges associated with building credibility in an environment that is characterized by significant volatility. It notes that in an emerging market environment exchange rate policy and inflation targeting cannot be easily dissociated because a history of monetary instability tends to make the exchange rate a focal point for inflationary expectations, and foreign currency borrowing subjects domesticfirmsand financial institutions to significant risks. The authors recommend a gradual learning process that includes high levels of communications and transparency on the part of the central bank.
Appendix. Data and Regression Results for Economic Performance Analysis
This appendix describes the data used in Section III and reports the detailed regression results that lie behind the key findings discussed with respect to economic performance across exchange rate regimes.
Much of the data are taken from Ghosh, Guide, and Wolf (2003), including the de jure classification of exchange rate regimes, the three measures of economic performance (inflation, growth, growth volatility), and the control (or explanatory) variables used in the regression analysis. Each variable is covered at an annual frequency from 1970 to 1999 for up to 158 countries. The control variables are drawn from the literature and are thought to provide a suitable explanation of the variations in the performance measures. Table A3.1 provides a detailed description of the data. It lists each variable, provides a brief description, and notes which of the subsequent regressions feature these variables. Using this data has the advantage of allowing the evaluation of performance under the Natural classification to be directly compared to a well-respected baseline that assesses performance across the de jure regimes.
Variable Description
Variable Description
| Variable | Description | Regression Used | |
|---|---|---|---|
| IMF de jure regime dummies | Pegged | Pegged regimes | 13.1,13.3,13.5 |
| Intermediate | Intermediate regimes | 13.1,13.3,13.5 | |
| Floating | Floating regimes | 13.1,13.3,13.5 | |
| Natural regime dummies | Pegged | Pegged regimes (fine classification 1~4) | 13.2,13.4,13.6,14.1~18.2 |
| Limited flexibility | Limited flexibility regimes (fine classification 5~9) | 14.1~18.2 | |
| Managed floating | Managed floating regimes (fine classification 10~12) | 14.1~18.2 | |
| Intermediate | Limited flexibility or managed floating regimes (fine classification 5~12) | 13.2,13.4,13.6 | |
| Freely floating | Freely floating regimes (fine classification 13) | 13.2,13.4,13.6,14.1~18.2 | |
| Freely falling | Freely falling regimes (fine classification 14) | 13.2,13.4,13.6,14.1~18.2 | |
| Dependent Variable | Control Variables | ||
| Inflation (scaled consumer price inflation; p/(1+p)) | Money growth | Broad money growth | 13.1,13.2,14.1~14.9,17.1,17.2,18.1,18.2 |
| Real GDP growth | Real GDP growth | 13.1,13.2, 14.1~14.9,17.1,17.2,18.1,18.2 | |
| Trade openness | Exports plus imports of goods and services (percent of GDP) | 13.1, 13.2, 14.1~14.9, 17.1, 17.2, 18.1, 18.2 | |
| Central bank turnover rate | Central bank governor turnover rate (per five years) | 13.1, 13.2, 14.1~14.9, 17.1, 17.2, 18.1, 18.2 | |
| Terms-of-trade growth | Terms-of-trade growth | 13.1,13.2,14.1~14.9,17.1,17.2,18.1,18.2 | |
| Government balance | Central government balance (percent of GDP) | 13.1,13.2,14.1~14.9,17.1,17.2,18.1,18.2 | |
| Common pegged | Overlap of natural classification pegged with IMF de jure pegged | 18.1 | |
| Common limited flexibility | Overlap of natural classification limited flexibility with IMF de jure intermediate | 18.1 | |
| Common managed floating | Overlap of natural classification managed floating with IMF de jure intermediate | 18.1 | |
| Common freely floating | Overlap of natural classification freely floating with IMF de jure floating | 18.1 | |
| Pegged duration | Linear time trend for pegged (natural) that measures regime duration | 18.2 | |
| Limited flexibility duration | Linear time trend for limited flexibility (natural) that measures regime duration | 18.2 | |
| Managed floating duration | Linear time trend for managed floating (natural) that measures regime duration | 18.2 | |
| Freely floating duration | Linear time trend for freely floating (natural) that measures regime duration | 18.2 | |
| Freely falling duration | Linear time trend for freely falling (natural) that measures regime duration | 18.2 | |
| Per capita real GDP growth | Investment ratio | Gross fixed investment (percent of GDP) | 13.3,13.4,15.1~15.9,17.3,17.4 |
| Trade openness | Exports plus imports of goods and services (percent of GDP) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Terms-of-trade growth | Terms-of-trade growth, three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Average years of schooling | Average number of years of schooling of total population age 25 and older (per five-years) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Tax ratio | General government revenue (percent of GDP), three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Government balance | Central government balance (percent of GDP), three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Initial income/U.S. income | Ratio of per capita GDP to U.S. per capita GDP in 1970 (international prices) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Population growth | Population growth, three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Population size | Population (logarithm) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Volatility of real GDP growth (threeyear centered standard deviation) | Investment ratio | Gross fixed investment (percent of GDP), three-year centered standard deviation | 13.5,13.6,16.1~16.9,17.5,17.6 |
| Trade openness | Exports plus imports of goods and services (percent of GDP) | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Terms-of-trade growth | Terms-of-trade growth, three-year centered standard deviation | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Average years of schooling | Average number of years of schooling of total population age 25 and older (per five years) | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Tax ratio | General government revenue (percent of GDP), three-year backward average | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Government balance | Central government balance (percent of GDP), three-year backward average | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Initial income/U.S. income | Ratio of per capita GDP to U.S. per capita GDP in 1970 (international prices) | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Population growth | Population growth, three-year backward average | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Crisis Variables | |||
| Bank crisis | From Demirgüç-Kunt and Detragiache (1998) | none | |
| Balance of payments crisis | From Berg, Borensztein and Pattillo (2004) | none |
Variable Description
| Variable | Description | Regression Used | |
|---|---|---|---|
| IMF de jure regime dummies | Pegged | Pegged regimes | 13.1,13.3,13.5 |
| Intermediate | Intermediate regimes | 13.1,13.3,13.5 | |
| Floating | Floating regimes | 13.1,13.3,13.5 | |
| Natural regime dummies | Pegged | Pegged regimes (fine classification 1~4) | 13.2,13.4,13.6,14.1~18.2 |
| Limited flexibility | Limited flexibility regimes (fine classification 5~9) | 14.1~18.2 | |
| Managed floating | Managed floating regimes (fine classification 10~12) | 14.1~18.2 | |
| Intermediate | Limited flexibility or managed floating regimes (fine classification 5~12) | 13.2,13.4,13.6 | |
| Freely floating | Freely floating regimes (fine classification 13) | 13.2,13.4,13.6,14.1~18.2 | |
| Freely falling | Freely falling regimes (fine classification 14) | 13.2,13.4,13.6,14.1~18.2 | |
| Dependent Variable | Control Variables | ||
| Inflation (scaled consumer price inflation; p/(1+p)) | Money growth | Broad money growth | 13.1,13.2,14.1~14.9,17.1,17.2,18.1,18.2 |
| Real GDP growth | Real GDP growth | 13.1,13.2, 14.1~14.9,17.1,17.2,18.1,18.2 | |
| Trade openness | Exports plus imports of goods and services (percent of GDP) | 13.1, 13.2, 14.1~14.9, 17.1, 17.2, 18.1, 18.2 | |
| Central bank turnover rate | Central bank governor turnover rate (per five years) | 13.1, 13.2, 14.1~14.9, 17.1, 17.2, 18.1, 18.2 | |
| Terms-of-trade growth | Terms-of-trade growth | 13.1,13.2,14.1~14.9,17.1,17.2,18.1,18.2 | |
| Government balance | Central government balance (percent of GDP) | 13.1,13.2,14.1~14.9,17.1,17.2,18.1,18.2 | |
| Common pegged | Overlap of natural classification pegged with IMF de jure pegged | 18.1 | |
| Common limited flexibility | Overlap of natural classification limited flexibility with IMF de jure intermediate | 18.1 | |
| Common managed floating | Overlap of natural classification managed floating with IMF de jure intermediate | 18.1 | |
| Common freely floating | Overlap of natural classification freely floating with IMF de jure floating | 18.1 | |
| Pegged duration | Linear time trend for pegged (natural) that measures regime duration | 18.2 | |
| Limited flexibility duration | Linear time trend for limited flexibility (natural) that measures regime duration | 18.2 | |
| Managed floating duration | Linear time trend for managed floating (natural) that measures regime duration | 18.2 | |
| Freely floating duration | Linear time trend for freely floating (natural) that measures regime duration | 18.2 | |
| Freely falling duration | Linear time trend for freely falling (natural) that measures regime duration | 18.2 | |
| Per capita real GDP growth | Investment ratio | Gross fixed investment (percent of GDP) | 13.3,13.4,15.1~15.9,17.3,17.4 |
| Trade openness | Exports plus imports of goods and services (percent of GDP) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Terms-of-trade growth | Terms-of-trade growth, three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Average years of schooling | Average number of years of schooling of total population age 25 and older (per five-years) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Tax ratio | General government revenue (percent of GDP), three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Government balance | Central government balance (percent of GDP), three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Initial income/U.S. income | Ratio of per capita GDP to U.S. per capita GDP in 1970 (international prices) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Population growth | Population growth, three-year backward average | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Population size | Population (logarithm) | 13.3,13.4,15.1~15.9,17.3,17.4 | |
| Volatility of real GDP growth (threeyear centered standard deviation) | Investment ratio | Gross fixed investment (percent of GDP), three-year centered standard deviation | 13.5,13.6,16.1~16.9,17.5,17.6 |
| Trade openness | Exports plus imports of goods and services (percent of GDP) | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Terms-of-trade growth | Terms-of-trade growth, three-year centered standard deviation | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Average years of schooling | Average number of years of schooling of total population age 25 and older (per five years) | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Tax ratio | General government revenue (percent of GDP), three-year backward average | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Government balance | Central government balance (percent of GDP), three-year backward average | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Initial income/U.S. income | Ratio of per capita GDP to U.S. per capita GDP in 1970 (international prices) | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Population growth | Population growth, three-year backward average | 13.5,13.6,16.1~16.9,17.5,17.6 | |
| Crisis Variables | |||
| Bank crisis | From Demirgüç-Kunt and Detragiache (1998) | none | |
| Balance of payments crisis | From Berg, Borensztein and Pattillo (2004) | none |
Three groups of variables are not covered in the Ghosh, Guide, and Wolf (2003) data. The first group is the Natural regime classification, available at an annual frequency from http://www.puaf.umd.edu/faculty/papers/reinhart/papers.htm.59 The second group is the crisis variables. The banking crisis variable is taken from Demirgüç-Kunt and Detragiache (1998). The authors declare a banking crisis to have occurred when any one of the following four conditions held: nonperforming loans exceeded 10 percent of banking system assets; a bailout cost 2 percent or more of GDP; large-scale nationalization occurred; or other emergency measures, such as bank holidays, deposit freezes, and special guarantees, had to be undertaken. The currency or balance of payments crisis variable is taken from Berg, Borensztein, and Pattillo (2004), which declares a crisis as having occurred when the weighted average of one-month changes in exchange rate and reserves is more than three (country-specific) standard deviations above the country average.
The final group of variables defines whether a country is classified as an advanced economy, an emerging market, or a developing country. Advanced countries are defined using the World Bank definition for upper-income countries, following Ghosh, Guide, and Wolf (2003). In dividing the rest of the world into two further groups, the analytical distinction of relevance was their degree of exposure to international capital markets. Those considered to have high exposure were classified as emerging markets, and the rest were designated developing.60 Table A3.2 lists the country composition of the advanced, emerging market, and developing country groups.
List of Countries
Emerging market economies are those that are included in the Morgan Stanley Capital International (MSCI) index. With the exception of Israel, which is in the MSCI index, advanced economies are those that are classified as upper-income economies by the World Bank. All other economies constitute the developing countries group.
List of Countries
| Advanced Countries | Emerging Markets1 | Developing Countries | ||
|---|---|---|---|---|
| Australia Austria Belgium Canada Cyprus Denmark Finland France Germany Greece Hong Kong SAR Iceland Ireland Italy Japan Kuwait Luxembourg Netherlands New Zealand Norway Portugal Qatar Singapore Slovenia Spain Sweden Switzerland United Arab Emirates United Kingdom United States | Argentina Brazil Chile China Colombia Czech Republic Egypt Hungary India Indonesia Israel Jordan Korea, Republic of Malaysia Mexico Morocco Pakistan Peru Philippines Poland Rep. Bolivariana de Venezuela Russian Federation South Africa Thailand Turkey | Albania Algeria Antigua and Barbuda Armenia Azerbaijan Bahrain, Kingdom of Bangladesh Barbados Belarus Belize Benin Bolivia Bosnia and Herzegovina Botswana Bulgaria Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. of Congo, Rep. of Costa Rica Cote d’lvoire Djibouti Dominica Dominican Republic Ecuador El Salvador Equatorial Guinea Estonia Ethiopia Fiji Gabon Gambia, The | Georgia Ghana Grenada Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Iran, Islamic Republic of Iraq Jamaica Kazakhstan Kenya Kyrgyz Republic Lao People’s Democratic Republic Latvia Lebanon Lesotho Liberia Libyan Arab Jamahiriya Lithuania Madagascar Malawi Maldives Mali Malta Mauritania Mauritius Moldova Mozambique Myanmar Nepal Nicaragua Niger Nigeria | Panama Papua New Guinea Paraguay Romania Rwanda St. Lucia St. Vincent and the Grenadines Samoa Senegal Seychelles Sierra Leone Slovak Republic Sri Lanka Sudan Suriname Swaziland Syrian Arab Republic Tajikistan Tanzania Togo Tonga Trinidad and Tobago Tunisia Turkmenistan Uganda Ukraine Uruguay Vietnam Zambia Zimbabwe |
Emerging market economies are those that are included in the Morgan Stanley Capital International (MSCI) index. With the exception of Israel, which is in the MSCI index, advanced economies are those that are classified as upper-income economies by the World Bank. All other economies constitute the developing countries group.
List of Countries
| Advanced Countries | Emerging Markets1 | Developing Countries | ||
|---|---|---|---|---|
| Australia Austria Belgium Canada Cyprus Denmark Finland France Germany Greece Hong Kong SAR Iceland Ireland Italy Japan Kuwait Luxembourg Netherlands New Zealand Norway Portugal Qatar Singapore Slovenia Spain Sweden Switzerland United Arab Emirates United Kingdom United States | Argentina Brazil Chile China Colombia Czech Republic Egypt Hungary India Indonesia Israel Jordan Korea, Republic of Malaysia Mexico Morocco Pakistan Peru Philippines Poland Rep. Bolivariana de Venezuela Russian Federation South Africa Thailand Turkey | Albania Algeria Antigua and Barbuda Armenia Azerbaijan Bahrain, Kingdom of Bangladesh Barbados Belarus Belize Benin Bolivia Bosnia and Herzegovina Botswana Bulgaria Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. of Congo, Rep. of Costa Rica Cote d’lvoire Djibouti Dominica Dominican Republic Ecuador El Salvador Equatorial Guinea Estonia Ethiopia Fiji Gabon Gambia, The | Georgia Ghana Grenada Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Iran, Islamic Republic of Iraq Jamaica Kazakhstan Kenya Kyrgyz Republic Lao People’s Democratic Republic Latvia Lebanon Lesotho Liberia Libyan Arab Jamahiriya Lithuania Madagascar Malawi Maldives Mali Malta Mauritania Mauritius Moldova Mozambique Myanmar Nepal Nicaragua Niger Nigeria | Panama Papua New Guinea Paraguay Romania Rwanda St. Lucia St. Vincent and the Grenadines Samoa Senegal Seychelles Sierra Leone Slovak Republic Sri Lanka Sudan Suriname Swaziland Syrian Arab Republic Tajikistan Tanzania Togo Tonga Trinidad and Tobago Tunisia Turkmenistan Uganda Ukraine Uruguay Vietnam Zambia Zimbabwe |
Emerging market economies are those that are included in the Morgan Stanley Capital International (MSCI) index. With the exception of Israel, which is in the MSCI index, advanced economies are those that are classified as upper-income economies by the World Bank. All other economies constitute the developing countries group.
To distinguish between emerging and developing economies, exposure to international capital can be determined either in a de jure sense (the extent of formal capital controls in place) or in a de facto sense (the actual exposure a country faces). In the spirit of this paper, a de facto definition was appropriate, an approach also followed by Prasad and others (2003). Because there are no well-defined or generally accepted thresholds of exposure to international capital, the cutoff between high and low exposure can be arbitrary and was dealt with by dropping and adding countries on the margin to check the robustness of the results. In this paper, the emerging markets are defined using the Morgan Stanley Capital International (MSCI) classification, which designates a country as an emerging market according to a number of factors: GDP per capita, local government regulations, perceived investment risk, foreign owner-ship limits and capital controls, and other factors. The main motivation for using this classification is that it captures the notion that these countries have access to international capital markets. See http://www.msci.com/equity/index.html for more information. In checking for the robustness of results presented, India and China, which are considered to have relatively closed capital accounts, were dropped from the emerging markets sample, but the results were unchanged. Countries added to the list included those that are not on the MSCI index but do appear on other international emerging market indices, and also such countries as Bahrain, Lebanon, and Tunisia that are not on any list but are thought of as relatively open to international capital markets. Again, the results were robust.
All regressions seek to identify the effects of the exchange rate regime, conditional on—or after taking into account—the influence of the conventional control variables relevant to that performance measure. All regressions also include two additional controls, which are not reported for brevity. First, common shocks across countries, such as spikes in oil prices or changes in the volatility of G-3 currencies, are controlled for through time dummies. Second, to control for unobserved, country-specific characteristics that are constant over time, country dummies are included. The implication of this approach is that regime performance is judged by changes that occur within a country rather than across countries. For comparison, however, this appendix also discusses below results without country fixed effects, hence taking into account differences across countries.
To briefly recap, the figures presented in Section III are based on these regressions. They present the coefficients on dummy, or categorical, variables representing the exchange rate regime. The dummy variable takes the value 1 if the exchange rate regime prevails in a country in a particular year; otherwise, it is assigned a value of zero. As is well known, when a set of dummy variables represents the full range of possibilities—in this case, the full range of exchange rate regimes—then regression analysis requires one of the possibilities to be left out. The regime that is left out is the base against which the others are compared. Hence, the coefficients presented in figures are to be interpreted as measures of performance (relative to the excluded pegged regime) and conditional upon the other included variables in the regression.
Table A3.3 (see page 41) compares economic performance (inflation, growth, and growth volatility) across regimes, contrasting the de jure classification with the Natural classification. Table A3.4 (see page 42) evaluates inflation performance across all countries: advanced, emerging market, and developing. Three different specifications are presented: the estimates with country markets fixed effects, on which the figures in the main text are based; the same specification but without fixed effects; and a specification with fixed effects but with the regime variables lagged by two years. The lagging of the exchange rate regime variables increases the likelihood, though does not ensure, that the results are reflecting the influence of regimes on performance rather than the other way around. Tables A3.5 and A3.6 (see pages 43 and 44) are analogous, except that they examine growth and growth volatility, respectively. The different specifications show that the qualitative direction of the key results presented in the main text hold up with remarkable consistency. Where the results across specifications are not similar—as for inflation in advanced countries or inflation and volatility in emerging markets—these are discussed in the text.
Comparing IMF De Jure and Natural Classifications1
Figures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Comparing IMF De Jure and Natural Classifications1
| Inflation | Per Capita Real GDP Growth | Volatility of Real GDP Growth | ||||
|---|---|---|---|---|---|---|
| Dependent Variable Classification | De jure | Natural | De jure | Natural | De jure | Natural |
| Regression number | 13.1 | 13.2 | 13.3 | 13.4 | 13.5 | 13.6 |
| Intermediate (de jure) | 0.062 | 0.000 | –0.001 | |||
| (6.58)*** | (–0.05) | (–0.31) | ||||
| Floating (de jure) | 0.062 | 0.003 | 0.008 | |||
| (5.13)*** | (0.57) | (3.11)*** | ||||
| Intermediate (natural) | 0.016 | 0.000 | 0.005 | |||
| (2.11)** | (0.00) | (1.19) | ||||
| Freely floating (natural) | 0.045 | 0.004 | 0.008 | |||
| (2.91)*** | (0.47) | (1.24) | ||||
| Freely falling (natural) | 0.218 | –0.025 | 0.012 | |||
| (13.51)*** | (–3.67)*** | (2.69)*** | ||||
| Money growth | 0.113 | 0.132 | ||||
| (0.83) | (1.05) | |||||
| Real GDP growth | –0.958 | –0.555 | ||||
| (–3.40)*** | (–2.59)*** | |||||
| Investment ratio | –0.083 | –0.090 | –0.019 | –0.012 | ||
| (–2.62)*** | (–2.83)*** | (–0.27) | (–0.17) | |||
| Trade openness | 0.022 | 0.027 | 0.025 | 0.029 | 0.007 | 0.008 |
| (1.29) | (1.90)* | (2.47)** | (2.94)*** | (1.06) | (1.22) | |
| Central bank turnover rate | 0.048 | 0.026 | ||||
| (3.34)*** | (2.05)** | |||||
| Terms-of-trade growth | –0.005 | 0.007 | 0.030 | 0.026 | 0.019 | 0.019 |
| (–0.25) | (0.39) | (2.09)** | (1.83)* | (2.02)** | (2.02)** | |
| Average years of schooling | 0.002 | 0.002 | 0.004 | 0.004 | ||
| (–0.83) | (–0.60) | (0.93) | (0.82) | |||
| Tax ratio | 0.004 | –0.006 | –0.010 | –0.005 | ||
| (0.14) | (–0.25) | (–0.76) | (–0.36) | |||
| Government balance | –0.361 | –0.239 | 0.008 | 0.004 | –0.008 | –0.003 |
| (–4.99)*** | (–4.07)*** | (0.25) | (–0.11) | (–0.40) | (–0.16) | |
| Initial income/U.S. income | –0.063 | –0.064 | –0.006 | –0.008 | ||
| (–2.51)** | (–2.39)** | (–0.40) | (0.55) | |||
| Population growth | –0.275 | –0.321 | 0.123 | 0.111 | ||
| (–1.68)* | (–1.90)* | (1.02) | (0.91) | |||
| Population size | 0.013 | 0.015 | ||||
| (1.01) | (1.07) | |||||
| Constant | 0.366 | 0.090 | 0.091 | 0.093 | 0.032 | 0.031 |
| (7.72)*** | (1.51) | (2.14)** | (2.07)** | (3.72)*** | (2.53)** | |
| Observations | 1,946 | 1,946 | 1,762 | 1,762 | 1,878 | 1,878 |
| R-squared | 0.58 | 0.70 | 0.29 | 0.31 | 0.26 | 0.26 |
Figures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Comparing IMF De Jure and Natural Classifications1
| Inflation | Per Capita Real GDP Growth | Volatility of Real GDP Growth | ||||
|---|---|---|---|---|---|---|
| Dependent Variable Classification | De jure | Natural | De jure | Natural | De jure | Natural |
| Regression number | 13.1 | 13.2 | 13.3 | 13.4 | 13.5 | 13.6 |
| Intermediate (de jure) | 0.062 | 0.000 | –0.001 | |||
| (6.58)*** | (–0.05) | (–0.31) | ||||
| Floating (de jure) | 0.062 | 0.003 | 0.008 | |||
| (5.13)*** | (0.57) | (3.11)*** | ||||
| Intermediate (natural) | 0.016 | 0.000 | 0.005 | |||
| (2.11)** | (0.00) | (1.19) | ||||
| Freely floating (natural) | 0.045 | 0.004 | 0.008 | |||
| (2.91)*** | (0.47) | (1.24) | ||||
| Freely falling (natural) | 0.218 | –0.025 | 0.012 | |||
| (13.51)*** | (–3.67)*** | (2.69)*** | ||||
| Money growth | 0.113 | 0.132 | ||||
| (0.83) | (1.05) | |||||
| Real GDP growth | –0.958 | –0.555 | ||||
| (–3.40)*** | (–2.59)*** | |||||
| Investment ratio | –0.083 | –0.090 | –0.019 | –0.012 | ||
| (–2.62)*** | (–2.83)*** | (–0.27) | (–0.17) | |||
| Trade openness | 0.022 | 0.027 | 0.025 | 0.029 | 0.007 | 0.008 |
| (1.29) | (1.90)* | (2.47)** | (2.94)*** | (1.06) | (1.22) | |
| Central bank turnover rate | 0.048 | 0.026 | ||||
| (3.34)*** | (2.05)** | |||||
| Terms-of-trade growth | –0.005 | 0.007 | 0.030 | 0.026 | 0.019 | 0.019 |
| (–0.25) | (0.39) | (2.09)** | (1.83)* | (2.02)** | (2.02)** | |
| Average years of schooling | 0.002 | 0.002 | 0.004 | 0.004 | ||
| (–0.83) | (–0.60) | (0.93) | (0.82) | |||
| Tax ratio | 0.004 | –0.006 | –0.010 | –0.005 | ||
| (0.14) | (–0.25) | (–0.76) | (–0.36) | |||
| Government balance | –0.361 | –0.239 | 0.008 | 0.004 | –0.008 | –0.003 |
| (–4.99)*** | (–4.07)*** | (0.25) | (–0.11) | (–0.40) | (–0.16) | |
| Initial income/U.S. income | –0.063 | –0.064 | –0.006 | –0.008 | ||
| (–2.51)** | (–2.39)** | (–0.40) | (0.55) | |||
| Population growth | –0.275 | –0.321 | 0.123 | 0.111 | ||
| (–1.68)* | (–1.90)* | (1.02) | (0.91) | |||
| Population size | 0.013 | 0.015 | ||||
| (1.01) | (1.07) | |||||
| Constant | 0.366 | 0.090 | 0.091 | 0.093 | 0.032 | 0.031 |
| (7.72)*** | (1.51) | (2.14)** | (2.07)** | (3.72)*** | (2.53)** | |
| Observations | 1,946 | 1,946 | 1,762 | 1,762 | 1,878 | 1,878 |
| R-squared | 0.58 | 0.70 | 0.29 | 0.31 | 0.26 | 0.26 |
Figures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Inflation Performance Across Country Groups1
Figures in parentheses are t-statistics;*significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Inflation Performance Across Country Groups1
| Advanced Countries | Emerging Markets | Developing Countries | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | ||
| Regression number | 14.1 | 14.2 | 14.3 | 14.4 | 14.5 | 14.6 | 14.7 | 14.8 | 14.9 | |
| Limited flexibility | –0.006 | 0.008 | –0.005 | –0.027 | –0.029 | –0.020 | 0.025 | 0.020 | 0.027 | |
| (–1.41) | (2.22)** | (–1.27) | (–1.45) | (–1.86)* | (–1.28) | (1.57) | (2.34)** | (1.96)** | ||
| Managed floating | –0.011 | 0.008 | –0.006 | –0.027 | 0.006 | 0.023 | 0.022 | 0.023 | 0.037 | |
| (–1.75)* | (1.56) | (–0.89) | (–1.40) | (0.41) | (1.64) | (1.27) | (2.85)*** | (2.86)*** | ||
| Freely floating | –0.014 | –0.018 | –0.01 | –0.012 | –0.010 | 0.059 | 0.104 | 0.091 | 0.065 | |
| (–2.11)** | (–4.52)*** | (–1.56) | (–0.36) | (–0.42) | (2.16)** | (3.83)*** | (3.87)*** | (2.65)*** | ||
| Freely falling | 0.221 | 0.302 | 0.139 | 0.234 | 0.322 | 0.244 | 0.232 | 0.288 | 0.149 | |
| (5.87)*** | (7.34)*** | (5.40)*** | (7.61)*** | (13.18)*** | (9.04)*** | (10.80)*** | (16.73)*** | (7.50)*** | ||
| Money growth | 0.725 | 0.283 | 0.088 | –0.032 | –0.097 | –0.011 | 0.010 | 0.015 | ||
| (2.65)*** | (16.55)*** | (5.06)*** | (–0.31) | (–1.02) | (–0.10) | (1.14) | (0.97) | (1.14) | 0.011 | |
| Real GDP growth | –0.397 | –0.468 | –0.205 | –1.498 | –2.025 | –1.656 | –0.442 | –0.874 | –0.640 | |
| (–2.31)** | (–2.33)** | (–1.03) | (–2.13)** | (–2.90)*** | (–2.12)** | (–1.58) | (–1.82)* | (–1.69)* | ||
| Trade openness | 0.008 | –0.004 | 0.000 | –0.008 | –0.008 | –0.003 | –0.032 | –0.012 | –0.033 | |
| (0.87) | (–1.40) | (0.00) | (–1.20) | (–1.04) | (–0.99) | (–2.70)*** | (–1.59) | (–2.87)*** | ||
| Central bank turnover rate | 0.006 | 0.017 | –0.017 | 0.094 | 0.152 | 0.148 | 0.044 | 0.022 | 0.063 | |
| (0.48) | (1.85)* | (–1.51) | (2.60)*** | (4.76)*** | (4.32)*** | (3.44)*** | (1.66)* | (4.39)*** | ||
| Terms-of-trade growth | 0.019 | 0.032 | 0.013 | –0.031 | –0.035 | –0.037 | –0.001 | –0.008 | –0.009 | |
| (2.13)** | (3.11)*** | (1.45) | (–0.79) | (–0.83) | (–0.87) | (–0.06) | (–0.45) | (–0.49) | ||
| Government balance | –0.208 | –0.188 | –0.199 | –0.557 | –0.175 | –0.677 | –0.210 | –0.221 | –0.324 | |
| (–4.42)*** | (–4.01)*** | (–3.21)*** | (–3.74)*** | (–1.64) | (–4.75)*** | (–2.77)*** | (–2.57)** | (–3.63)*** | ||
| Constant | –0.087 | 0.025 | 0.046 | 0.370 | 0.445 | 0.249 | 0.336 | 0.069 | 0.341 | |
| (–1.71)* | (2.91)*** | (1.41) | (101) | (1.35) | (0.62) | (3.63)*** | (2.49)** | (2.30)** | ||
| Observations | 701 | 701 | 701 | 617 | 617 | 617 | 1,401 | 1,401 | 1,401 | |
| R-squared | 0.82 | 0.73 | 0.83 | 0.73 | 0.68 | 0.71 | 0.67 | 0.44 | 0.57 | |
Figures in parentheses are t-statistics;*significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Inflation Performance Across Country Groups1
| Advanced Countries | Emerging Markets | Developing Countries | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | ||
| Regression number | 14.1 | 14.2 | 14.3 | 14.4 | 14.5 | 14.6 | 14.7 | 14.8 | 14.9 | |
| Limited flexibility | –0.006 | 0.008 | –0.005 | –0.027 | –0.029 | –0.020 | 0.025 | 0.020 | 0.027 | |
| (–1.41) | (2.22)** | (–1.27) | (–1.45) | (–1.86)* | (–1.28) | (1.57) | (2.34)** | (1.96)** | ||
| Managed floating | –0.011 | 0.008 | –0.006 | –0.027 | 0.006 | 0.023 | 0.022 | 0.023 | 0.037 | |
| (–1.75)* | (1.56) | (–0.89) | (–1.40) | (0.41) | (1.64) | (1.27) | (2.85)*** | (2.86)*** | ||
| Freely floating | –0.014 | –0.018 | –0.01 | –0.012 | –0.010 | 0.059 | 0.104 | 0.091 | 0.065 | |
| (–2.11)** | (–4.52)*** | (–1.56) | (–0.36) | (–0.42) | (2.16)** | (3.83)*** | (3.87)*** | (2.65)*** | ||
| Freely falling | 0.221 | 0.302 | 0.139 | 0.234 | 0.322 | 0.244 | 0.232 | 0.288 | 0.149 | |
| (5.87)*** | (7.34)*** | (5.40)*** | (7.61)*** | (13.18)*** | (9.04)*** | (10.80)*** | (16.73)*** | (7.50)*** | ||
| Money growth | 0.725 | 0.283 | 0.088 | –0.032 | –0.097 | –0.011 | 0.010 | 0.015 | ||
| (2.65)*** | (16.55)*** | (5.06)*** | (–0.31) | (–1.02) | (–0.10) | (1.14) | (0.97) | (1.14) | 0.011 | |
| Real GDP growth | –0.397 | –0.468 | –0.205 | –1.498 | –2.025 | –1.656 | –0.442 | –0.874 | –0.640 | |
| (–2.31)** | (–2.33)** | (–1.03) | (–2.13)** | (–2.90)*** | (–2.12)** | (–1.58) | (–1.82)* | (–1.69)* | ||
| Trade openness | 0.008 | –0.004 | 0.000 | –0.008 | –0.008 | –0.003 | –0.032 | –0.012 | –0.033 | |
| (0.87) | (–1.40) | (0.00) | (–1.20) | (–1.04) | (–0.99) | (–2.70)*** | (–1.59) | (–2.87)*** | ||
| Central bank turnover rate | 0.006 | 0.017 | –0.017 | 0.094 | 0.152 | 0.148 | 0.044 | 0.022 | 0.063 | |
| (0.48) | (1.85)* | (–1.51) | (2.60)*** | (4.76)*** | (4.32)*** | (3.44)*** | (1.66)* | (4.39)*** | ||
| Terms-of-trade growth | 0.019 | 0.032 | 0.013 | –0.031 | –0.035 | –0.037 | –0.001 | –0.008 | –0.009 | |
| (2.13)** | (3.11)*** | (1.45) | (–0.79) | (–0.83) | (–0.87) | (–0.06) | (–0.45) | (–0.49) | ||
| Government balance | –0.208 | –0.188 | –0.199 | –0.557 | –0.175 | –0.677 | –0.210 | –0.221 | –0.324 | |
| (–4.42)*** | (–4.01)*** | (–3.21)*** | (–3.74)*** | (–1.64) | (–4.75)*** | (–2.77)*** | (–2.57)** | (–3.63)*** | ||
| Constant | –0.087 | 0.025 | 0.046 | 0.370 | 0.445 | 0.249 | 0.336 | 0.069 | 0.341 | |
| (–1.71)* | (2.91)*** | (1.41) | (101) | (1.35) | (0.62) | (3.63)*** | (2.49)** | (2.30)** | ||
| Observations | 701 | 701 | 701 | 617 | 617 | 617 | 1,401 | 1,401 | 1,401 | |
| R-squared | 0.82 | 0.73 | 0.83 | 0.73 | 0.68 | 0.71 | 0.67 | 0.44 | 0.57 | |
Figures in parentheses are t-statistics;*significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Growth Performance Across Country Groups1
Figures in parentheses are t-statistics;*significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.
Growth Performance Across Country Groups1
| Advanced Countries | Emerging Markets | Developing Countries | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | |
| Regression number | 15.1 | 15.2 | 15.3 | 15.4 | 15.5 | 15.6 | 15.7 | 15.8 | 15.9 |
| Limited flexibility | 0.001 | 0.002 | 0.008 | 0.003 | 0.004 | –0.007 | –0.005 | 0.014 | 0.006 |
| (0.14) | (0.49) | (1.01) | (0.34) | (0.57) | (–0.56) | (–0.71) | (3.54)*** | (0.79) | |
| Managed floating | 0.005 | 0.010 | 0.019 | 0.020 | 0.010 | 0.002 | –0.008 | 0.010 | –0.005 |
| (0.56) | (1.13) | (1.69)* | (1.52) | (1.12) | (0.19) | (–1.28) | (2.42)** | (–0.86) | |
| Freely floating | 0.027 | 0.024 | 0.021 | –0.025 | –0.015 | –0.020 | –0.017 | –0.006 | 0.002 |
| (1.97)** | (1.93)* | (1.64) | (–0.88) | (–0.85) | (–0.47) | (–1.03) | (–0.43) | (0.15) | |
| Freely falling | –0.029 | –0.012 | –0.003 | –0.045 | –0.035 | –0.023 | –0.032 | –0.019 | –0.002 |
| (–1.02) | (–0–54) | (–0.13) | (–3.96)*** | (–4.06)*** | (–1.24) | (–4.29)*** | (–3.21)*** | (–0.31) | |
| Investment ratio | 0.453 | 0.265 | 0.428 | –0.048 | 0.062 | –0.037 | –0.033 | 0.039 | –0.025 |
| (1.33) | (1.35) | (1.25) | (–0.51) | (0.76) | (–0.37) | (–0.79) | (1.41) | (–0.58) | |
| Trade openness | –0.016 | 0.016 | –0.013 | –0.006 | –0.006 | –0.013 | 0.009 | 0.016 | 0.006 |
| (–0.33) | (1.76)* | (–0.28) | (–0.19) | (–0.32) | (–0.35) | (0.73) | (2.39)** | (0.43) | |
| Terms-of-trade growth | 0.305 | 0.383 | 0.310 | 0.011 | 0.001 | 0.036 | –0.004 | 0.019 | –0.006 |
| (1.32) | (1.26) | (1.34) | (0.32) | (0.03) | (0.93) | (–0.21) | (0.98) | (–0.31) | |
| Average years of schooling | 0.008 | 0.004 | 0.009 | 0.017 | 0.005 | 0.015 | –0.010 | 0.001 | –0.014 |
| (1.21) | (1.43) | (1.36) | (1.22) | (1.33) | (1.06) | (–2.02)** | (0.77) | (–2.71)*** | |
| Tax ratio | 0.079 | 0.085 | 0.059 | –0.047 | –0.010 | –0.029 | –0.011 | –0.028 | –0.013 |
| (1.41) | (1.47) | (1.01) | (–1.02) | (–0.30) | (–0.65) | (–0.84) | (–2.78)*** | (–0.94) | |
| Government balance | –0.520 | –0.448 | –0.526 | –0.277 | –0.086 | –0.233 | 0.070 | 0.046 | 0.073 |
| (–1.64) | (–1.57) | (–1.64) | (–3.37)*** | (–1.34) | (–2.75)*** | (1.77)* | (1.62) | (1.78)* | |
| Initial income/U.S. income | 0.087 | –0.025 | 0.106 | –0.285 | –0.059 | –0.191 | –0.022 | –0.034 | 0.015 |
| (1.71)* | (–0.91) | (1.96)* | (–2.00)** | (–2.30)** | (–1.67)* | (–0.41) | (–3.11)*** | (0.27) | |
| Population growth | 1.275 | 0.716 | 1.366 | –0.196 | 0.144 | –0.255 | –0.679 | –0.432 | –0.680 |
| (1.04) | (0.84) | (1.08) | (–0.35) | (0.41) | (–0.44) | (–1.95)* | (–2.08)** | (–1.88)* | |
| Population size | –0.412 | –0.002 | –0.432 | 0.029 | 0.003 | 0.034 | –0.020 | 0.002 | –0.003 |
| (–2.07)** | (–0.85) | (–2.09)** | (0.94) | (0.89) | (0.90) | (–0.84) | (0.83) | (–0.11) | |
| Constant | –0.822 | –0.070 | –0.865 | –0.032 | –0.003 | –0.074 | 0.101 | 0.030 | 0.070 |
| (–1.85)* | (–0.77) | (–1.88)* | (–0.27) | (0.12) | (–0.55) | (1.20) | (2.27)** | (0.76) | |
| Observations | 629 | 629 | 620 | 529 | 529 | 520 | 1,228 | 1,228 | 1,209 |
| R-squared | 0.37 | 0.28 | 0.38 | 0.30 | 0.20 | 0.23 | 0.25 | 0.15 | 0.23 |
Figures in parentheses are t-statistics;*significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.
Growth Performance Across Country Groups1
| Advanced Countries | Emerging Markets | Developing Countries | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | |
| Regression number | 15.1 | 15.2 | 15.3 | 15.4 | 15.5 | 15.6 | 15.7 | 15.8 | 15.9 |
| Limited flexibility | 0.001 | 0.002 | 0.008 | 0.003 | 0.004 | –0.007 | –0.005 | 0.014 | 0.006 |
| (0.14) | (0.49) | (1.01) | (0.34) | (0.57) | (–0.56) | (–0.71) | (3.54)*** | (0.79) | |
| Managed floating | 0.005 | 0.010 | 0.019 | 0.020 | 0.010 | 0.002 | –0.008 | 0.010 | –0.005 |
| (0.56) | (1.13) | (1.69)* | (1.52) | (1.12) | (0.19) | (–1.28) | (2.42)** | (–0.86) | |
| Freely floating | 0.027 | 0.024 | 0.021 | –0.025 | –0.015 | –0.020 | –0.017 | –0.006 | 0.002 |
| (1.97)** | (1.93)* | (1.64) | (–0.88) | (–0.85) | (–0.47) | (–1.03) | (–0.43) | (0.15) | |
| Freely falling | –0.029 | –0.012 | –0.003 | –0.045 | –0.035 | –0.023 | –0.032 | –0.019 | –0.002 |
| (–1.02) | (–0–54) | (–0.13) | (–3.96)*** | (–4.06)*** | (–1.24) | (–4.29)*** | (–3.21)*** | (–0.31) | |
| Investment ratio | 0.453 | 0.265 | 0.428 | –0.048 | 0.062 | –0.037 | –0.033 | 0.039 | –0.025 |
| (1.33) | (1.35) | (1.25) | (–0.51) | (0.76) | (–0.37) | (–0.79) | (1.41) | (–0.58) | |
| Trade openness | –0.016 | 0.016 | –0.013 | –0.006 | –0.006 | –0.013 | 0.009 | 0.016 | 0.006 |
| (–0.33) | (1.76)* | (–0.28) | (–0.19) | (–0.32) | (–0.35) | (0.73) | (2.39)** | (0.43) | |
| Terms-of-trade growth | 0.305 | 0.383 | 0.310 | 0.011 | 0.001 | 0.036 | –0.004 | 0.019 | –0.006 |
| (1.32) | (1.26) | (1.34) | (0.32) | (0.03) | (0.93) | (–0.21) | (0.98) | (–0.31) | |
| Average years of schooling | 0.008 | 0.004 | 0.009 | 0.017 | 0.005 | 0.015 | –0.010 | 0.001 | –0.014 |
| (1.21) | (1.43) | (1.36) | (1.22) | (1.33) | (1.06) | (–2.02)** | (0.77) | (–2.71)*** | |
| Tax ratio | 0.079 | 0.085 | 0.059 | –0.047 | –0.010 | –0.029 | –0.011 | –0.028 | –0.013 |
| (1.41) | (1.47) | (1.01) | (–1.02) | (–0.30) | (–0.65) | (–0.84) | (–2.78)*** | (–0.94) | |
| Government balance | –0.520 | –0.448 | –0.526 | –0.277 | –0.086 | –0.233 | 0.070 | 0.046 | 0.073 |
| (–1.64) | (–1.57) | (–1.64) | (–3.37)*** | (–1.34) | (–2.75)*** | (1.77)* | (1.62) | (1.78)* | |
| Initial income/U.S. income | 0.087 | –0.025 | 0.106 | –0.285 | –0.059 | –0.191 | –0.022 | –0.034 | 0.015 |
| (1.71)* | (–0.91) | (1.96)* | (–2.00)** | (–2.30)** | (–1.67)* | (–0.41) | (–3.11)*** | (0.27) | |
| Population growth | 1.275 | 0.716 | 1.366 | –0.196 | 0.144 | –0.255 | –0.679 | –0.432 | –0.680 |
| (1.04) | (0.84) | (1.08) | (–0.35) | (0.41) | (–0.44) | (–1.95)* | (–2.08)** | (–1.88)* | |
| Population size | –0.412 | –0.002 | –0.432 | 0.029 | 0.003 | 0.034 | –0.020 | 0.002 | –0.003 |
| (–2.07)** | (–0.85) | (–2.09)** | (0.94) | (0.89) | (0.90) | (–0.84) | (0.83) | (–0.11) | |
| Constant | –0.822 | –0.070 | –0.865 | –0.032 | –0.003 | –0.074 | 0.101 | 0.030 | 0.070 |
| (–1.85)* | (–0.77) | (–1.88)* | (–0.27) | (0.12) | (–0.55) | (1.20) | (2.27)** | (0.76) | |
| Observations | 629 | 629 | 620 | 529 | 529 | 520 | 1,228 | 1,228 | 1,209 |
| R-squared | 0.37 | 0.28 | 0.38 | 0.30 | 0.20 | 0.23 | 0.25 | 0.15 | 0.23 |
Figures in parentheses are t-statistics;*significant at 10 percent; **significant at 5 percent; ***significant at 1 percent.
Volatility of Real GDP Growth Performance Across Country Groups1
igures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Volatility of Real GDP Growth Performance Across Country Groups1
| Advanced Countries | Emerging Markets | Developing Countries | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | |
| Regression number | 16.1 | 16.2 | 16.3 | 16.4 | 16.5 | 16.6 | 16.7 | 16.8 | 16.9 |
| Limited flexibility | 0.006 | 0.002 | 0.009 | 0.004 | –0.004 | –0.018 | –0.005 | –0.010 | 0.002 |
| (1.08) | (0.52) | (1.72)* | (0.56) | (–1.08) | (–2.14)** | (–1.13) | (–4.28)*** | (0.59) | |
| Managed floating | 0.011 | 0.009 | 0.010 | 0.027 | 0.009 | –0.009 | –0.001 | –0.002 | 0.002 |
| (1.96)* | (1.85)* | (1.83)* | (2.24)** | (1.29) | (–1.04) | (–0.40) | (–1.03) | (0.63) | |
| Freely floating | 0.013 | 0.011 | 0.014 | 0.036 | 0.012 | –0.031 | 0.001 | 0.005 | –0.002 |
| (1.86)* | (1.79)* | (1.99)** | (1.59) | (0.84) | (–1.48) | (0.14) | (0.60) | (–0.31) | |
| Freely falling | –0.005 | –0.002 | 0.004 | 0.021 | 0.020 | –0.007 | 0.007 | 0.008 | 0.004 |
| (–0.48) | (–0.24) | (0.42) | (3.03)*** | (4.16)*** | (–0.73) | (1.63) | (2.25)** | (1.00) | |
| Investment ratio | –0.537 | 0.266 | –0.559 | –0.148 | –0.110 | –0.134 | –0.049 | –0.003 | –0.057 |
| (–1.05) | (0.65) | (–1.10) | (–1.07) | (–0.79) | (–0.98) | (–0.70) | (–0.05) | (–0.82) | |
| Trade openness | 0.047 | 0.018 | 0.048 | 0.039 | 0.024 | 0.049 | 0.007 | 0.000 | 0.004 |
| (1.08) | (3.37)*** | (1.12) | (2.24)** | (2.57)** | (2.38)** | (0.92) | (–0.01) | (0.47) | |
| Terms-of-trade growth | 0.068 | 0.145 | 0.069 | 0.102 | 0.066 | 0.092 | 0.021 | 0.018 | 0.022 |
| (1.16) | (2.36)** | (1.20) | (3.50)*** | (2.14)** | (3.20)*** | (1.70)* | (1.42) | (1.73)* | |
| Average years of schooling | 0.001 | –0.003 | 0.001 | 0.012 | 0.006 | 0.015 | 0.000 | –0.002 | 0.000 |
| (0.31) | (–2.65)*** | (0.30) | (1.20) | (2.09)** | (1.51) | (0.03) | (–2.62)*** | (–0.05) | |
| Tax ratio | 0.013 | 0.006 | 0.013 | 0.032 | –0.052 | 0.052 | –0.009 | 0.018 | –0.009 |
| (0.33) | (0.30) | (0.32) | (1.37) | (–3.04)*** | (2.04)** | (–0.98) | (2.48)** | (–0.99) | |
| Government balance | –0.155 | –0.103 | –0.157 | 0.001 | –0.098 | –0.033 | –0.022 | –0.040 | –0.028 |
| (–1.31) | (–1.13) | (–1.32) | (0.01) | (–1.99)** | (–0.34) | (–0.95) | (–2.34)** | (–1.16) | |
| Initial income/U.S. income | 0.137 | 0.046 | 0.139 | –0.263 | –0.037 | –0.244 | 0.013 | 0.002 | –0.001 |
| (1.94)* | (3.52)*** | (1.96)* | (–3.00)*** | (–1.65)* | (–2.71)*** | (1.21) | (0.31) | (–0.07) | |
| Population growth | –0.013 | 0.341 | 0.002 | –0.398 | 0.570 | –0.343 | –0.089 | –0.018 | –0.088 |
| (–0.03) | (0.90) | (0.00) | (–0.72) | (1.40) | (–0.67) | (–0.-33) | (–0.11) | (–0.32) | |
| Constant | –0.131 | 0.007 | –0.155 | 0.029 | –0.015 | 0.034 | 0.033 | 0.040 | 0.048 |
| (–0.72) | (0.32) | (–0.90) | (1.18) | (–0.76) | (1.40) | (2.17)** | (4.59)*** | (3.00)*** | |
| Observations | 617 | 617 | 617 | 518 | 518 | 518 | 1,201 | 1,201 | 1,201 |
| R-squared | 0.50 | 0.40 | 0.50 | 0.36 | 0.20 | 0.33 | 0.28 | 0.10 | 0.28 |
igures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Volatility of Real GDP Growth Performance Across Country Groups1
| Advanced Countries | Emerging Markets | Developing Countries | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | Country fixed effects | No country fixed effects | Country fixed effects with two-year lagged regime variables | |
| Regression number | 16.1 | 16.2 | 16.3 | 16.4 | 16.5 | 16.6 | 16.7 | 16.8 | 16.9 |
| Limited flexibility | 0.006 | 0.002 | 0.009 | 0.004 | –0.004 | –0.018 | –0.005 | –0.010 | 0.002 |
| (1.08) | (0.52) | (1.72)* | (0.56) | (–1.08) | (–2.14)** | (–1.13) | (–4.28)*** | (0.59) | |
| Managed floating | 0.011 | 0.009 | 0.010 | 0.027 | 0.009 | –0.009 | –0.001 | –0.002 | 0.002 |
| (1.96)* | (1.85)* | (1.83)* | (2.24)** | (1.29) | (–1.04) | (–0.40) | (–1.03) | (0.63) | |
| Freely floating | 0.013 | 0.011 | 0.014 | 0.036 | 0.012 | –0.031 | 0.001 | 0.005 | –0.002 |
| (1.86)* | (1.79)* | (1.99)** | (1.59) | (0.84) | (–1.48) | (0.14) | (0.60) | (–0.31) | |
| Freely falling | –0.005 | –0.002 | 0.004 | 0.021 | 0.020 | –0.007 | 0.007 | 0.008 | 0.004 |
| (–0.48) | (–0.24) | (0.42) | (3.03)*** | (4.16)*** | (–0.73) | (1.63) | (2.25)** | (1.00) | |
| Investment ratio | –0.537 | 0.266 | –0.559 | –0.148 | –0.110 | –0.134 | –0.049 | –0.003 | –0.057 |
| (–1.05) | (0.65) | (–1.10) | (–1.07) | (–0.79) | (–0.98) | (–0.70) | (–0.05) | (–0.82) | |
| Trade openness | 0.047 | 0.018 | 0.048 | 0.039 | 0.024 | 0.049 | 0.007 | 0.000 | 0.004 |
| (1.08) | (3.37)*** | (1.12) | (2.24)** | (2.57)** | (2.38)** | (0.92) | (–0.01) | (0.47) | |
| Terms-of-trade growth | 0.068 | 0.145 | 0.069 | 0.102 | 0.066 | 0.092 | 0.021 | 0.018 | 0.022 |
| (1.16) | (2.36)** | (1.20) | (3.50)*** | (2.14)** | (3.20)*** | (1.70)* | (1.42) | (1.73)* | |
| Average years of schooling | 0.001 | –0.003 | 0.001 | 0.012 | 0.006 | 0.015 | 0.000 | –0.002 | 0.000 |
| (0.31) | (–2.65)*** | (0.30) | (1.20) | (2.09)** | (1.51) | (0.03) | (–2.62)*** | (–0.05) | |
| Tax ratio | 0.013 | 0.006 | 0.013 | 0.032 | –0.052 | 0.052 | –0.009 | 0.018 | –0.009 |
| (0.33) | (0.30) | (0.32) | (1.37) | (–3.04)*** | (2.04)** | (–0.98) | (2.48)** | (–0.99) | |
| Government balance | –0.155 | –0.103 | –0.157 | 0.001 | –0.098 | –0.033 | –0.022 | –0.040 | –0.028 |
| (–1.31) | (–1.13) | (–1.32) | (0.01) | (–1.99)** | (–0.34) | (–0.95) | (–2.34)** | (–1.16) | |
| Initial income/U.S. income | 0.137 | 0.046 | 0.139 | –0.263 | –0.037 | –0.244 | 0.013 | 0.002 | –0.001 |
| (1.94)* | (3.52)*** | (1.96)* | (–3.00)*** | (–1.65)* | (–2.71)*** | (1.21) | (0.31) | (–0.07) | |
| Population growth | –0.013 | 0.341 | 0.002 | –0.398 | 0.570 | –0.343 | –0.089 | –0.018 | –0.088 |
| (–0.03) | (0.90) | (0.00) | (–0.72) | (1.40) | (–0.67) | (–0.-33) | (–0.11) | (–0.32) | |
| Constant | –0.131 | 0.007 | –0.155 | 0.029 | –0.015 | 0.034 | 0.033 | 0.040 | 0.048 |
| (–0.72) | (0.32) | (–0.90) | (1.18) | (–0.76) | (1.40) | (2.17)** | (4.59)*** | (3.00)*** | |
| Observations | 617 | 617 | 617 | 518 | 518 | 518 | 1,201 | 1,201 | 1,201 |
| R-squared | 0.50 | 0.40 | 0.50 | 0.36 | 0.20 | 0.33 | 0.28 | 0.10 | 0.28 |
igures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Table A3.7 (see page 45) reports results for emerging markets in the 1990s and shows that exposure to international capital markets became widespread mainly in that decade. Table A3.8 (see page 46) reports the inflation regression results, which include regime-specific announcement and duration variables. Finally, Table A3.9 (see page 47) summarizes all other robustness tests, which have been omitted for brevity.
Emerging Markets in the 1990s1
Figures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Emerging Markets in the 1990s1
| Inflation | Per Capita GDP Growth | Volatility of Real GDP Growth | ||||
|---|---|---|---|---|---|---|
| Dependent Variable | No lag | Two-year lagged regime variables | No lag | Two-year lagged regime variables | No lag | Two-year lagged regime variables |
| Regression number | 17.1 | 17.2 | 17.3 | 17.4 | 17.5 | 17.6 |
| Limited flexibility | –0.028 | 0.003 | 0.005 | –0.029 | –0.011 | –0.035 |
| (–0.74) | (0.11) | (0.38) | (–0.95) | (–1.14) | (–1.87)* | |
| Managed floating | –0.055 | 0.011 | 0.008 | –0.026 | 0.024 | –0.030 |
| (–1.25) | (0.34) | (0.54) | (–0.80) | (2.52)** | (–1.33) | |
| Freely floating | –0.036 | 0.213 | –0.039 | –0.019 | –0.011 | –0.090 |
| (–0.59) | (2.74)*** | (–0.92) | (–0.34) | (–0.30) | (–1.69)* | |
| Freely falling | 0.137 | 0.187 | –0.056 | –0.020 | 0.023 | –0.034 |
| (1.99)** | (3.46)*** | (–3.15)*** | (–0.67) | (2.11)** | (–1.55) | |
| Money growth | 0.034 | 0.034 | ||||
| (2.24)** | (2.41)** | |||||
| Real GDP growth | –1.096 | –2.207 | ||||
| (–1.10) | (–1.65) | |||||
| Investment ratio | –0.781 | –0.581 | –0.954 | –0.622 | ||
| (–3.28)*** | (–3.00)*** | (–1.70)* | (–1.29) | |||
| Trade openness | 0.229 | 0.341 | –0.053 | –0.105 | 0.067 | 0.084 |
| (2.78)*** | (3.24)*** | (–1.15) | (–2.22)** | (2.47)** | (2.42)** | |
| Central bank turnover rate | 0.074 | 0.067 | ||||
| (1.20) | (0.99) | |||||
| Terms-of-trade growth | 0.006 | 0.061 | –0.101 | –0.062 | 0.133 | 0.160 |
| (0.05) | (0.41) | (–1.11) | (–0.63) | (1.84)* | (2.06)** | |
| Average years of schooling | 0.030 | 0.031 | 0.049 | 0.045 | ||
| (1.02) | (1.28) | (2.56)** | (2.63)*** | |||
| Tax ratio | –0.382 | –0.278 | 0.033 | –0.088 | ||
| (–2.87)*** | (–2.01)** | (0.45) | (–1.13) | |||
| Government balance | –0.628 | –0.624 | 0.452 | 0.395 | –0.268 | –0.326 |
| (–1.24) | (–1.15) | (2.02)** | (1.90)* | (–1.44) | (–1.46) | |
| Initial income/U.S. income | –1.788 | –1.973 | –0.555 | –0.454 | ||
| (–2.67)*** | (–3.16)*** | (–3.94)*** | (–3.87)*** | |||
| Population growth | –1.418 | –1.561 | –1.894 | –1.613 | ||
| (–0.75) | (–0.93) | (–1.44) | (–1.45) | |||
| Population size | –0.829 | –0.977 | ||||
| (–2.82)*** | (–3.41)*** | |||||
| Constant | 0.148 | 0.240 | 4.027 | 4.507 | –0.099 | –0.046 |
| (1.25) | (1.68)* | (3.06)*** | (3.50)*** | (–1.64) | (–0.82) | |
| Observations | 239 | 239 | 230 | 230 | 230 | 230 |
| R-squared | 0.80 | 0.79 | 0.52 | 0.47 | 0.57 | 0.55 |
Figures in parentheses are t-statistics; *significant at 10 percent;**significant at 5 percent;***significant at 1 percent.
Emerging Markets in the 1990s1
| Inflation | Per Capita GDP Growth | Volatility of Real GDP Growth | ||||
|---|---|---|---|---|---|---|
| Dependent Variable | No lag | Two-year lagged regime variables | No lag | Two-year lagged regime variables | No lag | Two-year lagged regime variables |
| Regression number | 17.1 | 17.2 | 17.3 | 17.4 | 17.5 | 17.6 |
| Limited flexibility | –0.028 | 0.003 | 0.005 | –0.029 | –0.011 | –0.035 |
| (–0.74) | (0.11) | (0.38) | (–0.95) | (–1.14) | (–1.87)* | |
| Managed floating | –0.055 | 0.011 | 0.008 | –0.026 | 0.024 | –0.030 |
| (–1.25) | (0.34) | (0.54) | (–0.80) | (2.52)** | (–1.33) | |
| Freely floating | –0.036 | 0.213 | –0.039 | –0.019 | –0.011 | –0.090 |
| (–0.59) | (2.74)*** | (–0.92) | ||||