Chapter

VII Disintermediation and Monetary Transmission

Author(s):
Vladimir Klyuev, Martin Mühleisen, and Tamim Bayoumi
Published Date:
October 2007
Share
  • ShareShare
Show Summary Details
Author(s)
Jorge E. Roldos

The financial system links monetary policy and the real economy. Thus, events or trends that affect the financial system also can change the monetary transmission mechanism. Over the last two decades, Canada’s financial system (like those in other industrialized countries) has been transformed by several rounds of financial deregulation, innovation, and disintermediation. This transformation has likely affected the transmission of monetary policy.

Monetary transmission occurs through the traditional channel (the impact of interest rates on components of aggregate demand) and through the so-called credit channel, including constraints in the availability of loanable funds to banks and corporates. Those who stress the predominance of the credit channel argue that the traditional channel cannot explain the magnitude, timing, and compositional effects of the monetary policy actions in the U.S. economy (see Bernanke and Gertler, 1995). Credit market frictions give rise to a “financial accelerator” mechanism that amplifies and makes more persistent the impact of a monetary policy action on the economy. These credit market frictions depend on several features of the financial system, in particular the degree to which the financial system is securitized (broadly understood as the development of securities markets versus banks) and the size and the state of the banking system (Cecchetti, 1999).

The credit channel is more an enhancement mechanism than a truly independent or parallel channel of monetary transmission (Bernanke and Gertler, 1995). Earlier literature on the credit channel focused on the bank lending channel and argued that monetary policy operated through the lack of substitutes in both the liability and asset sides of banks’ balance sheets. In particular, it was argued, a monetary tightening would reduce excess reserves and contract the supply of loans, and this would have a direct negative impact on output. The evidence on this mechanism is somewhat mixed (see, for instance, Kashyap and Stein, 1994), and it is likely that, with financial deregulation and innovation, the importance of the bank lending channel has diminished. More recent literature has focused on a broader balance sheet channel and argues that a monetary contraction weakens firms’ financial positions— either directly through reduced cash flows or indirectly through the declining value of assets and/or collateral. The deterioration in firms’ financial condition increases the external finance premium, and the associated increase in the cost of capital operates through the financial accelerator mechanism (Bernanke, Gertler, and Gilchrist, 1999). Recent evidence on the macro-economic significance of these financial frictions is provided in Levin, Natalucci, and Zakrajsek (2004).

This section uses two methodologies to study changes in Canada’s monetary policy transmission associated with important changes in the financial structure during the 1990s. First, a series of vector autoregression (VAR) models is used to characterize the dynamics of output and prices after a monetary shock. Standard VAR models used to study monetary transmission of the type surveyed in Christiano, Eichenbaum, and Evans (1999) are extended with the inclusion of financial variables emphasized in the credit channel literature and are tested for the existence of structural breaks or parameter instability around the dates of major changes in financial sector regulation. Second, this section studies the impact of financial variables on structural econometric models of aggregate demand, which are increasingly used by central banks to conduct monetary policy analysis. In particular, it gauges the impact of the ratio of direct (or market) to indirect (or intermediated) finance—a summary measure of disintermediation—on the interest rate sensitivity of aggregate demand.

Financial Deregulation and Disintermediation

The Canadian financial system underwent two important changes over the last two decades as a result of deregulation and financial innovation.1 First, it became more market based, as corporates increased the use of direct (or market) financing compared to indirect (or intermediated) financing. Second, there was an increase in households’ access to credit, reflected in the rise in consumer and mortgage credit.

The first trend is apparent in Figure 7.1. During the 1970s, the rise in inflation and nominal interest rate uncertainty led the corporate sector to rely increasingly on short-term bank loans and much less on issuing securities. However, this trend was reversed in the 1980s, and bank lending declined as a source of funding for the corporate sector from approximately 60 percent in 1980 to less than 40 percent in the 2000s. This was accompanied by an increase in the issuance of corporate bonds and commercial paper (Figure 7.2).

Figure 7.1.Nonfinancial Corporate Financing Sources, 1971–2005

(Stocks outstanding, in percent of total)

Source: Bank of Canada.

Figure 7.2.Credit Flows, 1971–2005

(In billions of Canadian dollars)

Source: Bank of Canada.

This process of disintermediation is likely to have reduced both the bank dependency of borrowers and the constraints on the availability of loanable funds,2 which together would indicate a decline in the relative importance of the bank lending channel. However, they do not necessarily imply a reduction in the importance of the credit channel because the cost of external finance, summarized in the “external finance premium,” may still operate as a key mechanism for the transmission of monetary policy.

Changes in the regulatory framework, together with changes in global and Canadian financial market conditions, were major drivers of these structural changes. Calmes (2004) notes that significant amendments to the Bank Act in 1980, 1987, 1992, and 1997 contributed to (and were in part driven by) the sharp change in corporates’ funding mix. Figure 7.3 shows the increase in the ratio of direct to indirect lending beginning in the late 1980s and lasting through the 1990s, following a decade of stagnation and a decline during the 1970s.

Figure 7.3.Ratio of Direct to Indirect Private Lending, 1971–2005

Source: Bank of Canada.

This pattern of disintermediation, which parallels changes in other countries, was accompanied by a switch in banks’ activities, from lending to large corporates to underwriting and other securities-related activities. In particular, the 1987 amendments to the Bank Act allowed banks to conduct brokerage activities (Calmes, 2004), and banks made substantial investments in this area between 1987 and 1989. Nonetheless, banks continue to be the main providers of loans to small and medium-size enterprises. Also, several indicators show that the Canadian banking system has continued to grow despite banks’ declining share of lending, especially when off-balance-sheet activities are included (see Calmes, 2004).

The second trend is the growth in credit to the household sector (broadly defined as persons and unincorporated businesses), which rose from just under 50 percent of GDP in the early 1980s to almost 70 percent of GDP in 2001 (see Freedman and Engert, 2003). This steady increase was driven by the growth in consumer and mortgage credit, associated with the decline in inflation and the escalation of housing prices (Figure 7.4). Indeed, consumer credit as a share of the total (business and consumer credit), increased from 42 percent in 1982 to 55 percent in 2005.

Figure 7.4.Outstanding Credit, 1971–2005

(In billions of Canadian dollars)

Source: Bank of Canada.

The growth in credit to households, which was also shared by other industrialized nations, raised the importance of the household sector and opened the potential for restrengthening the bank lending channel and/or the financial accelerator (which would work more directly through housing prices and collateral). Although the securitization of mortgages has had a profound impact on monetary transmission in the United States (Estrella, 2002), mortgage securitization has advanced at a much slower pace in Canada (Freedman and Engert, 2003). The following subsections explore how financial variables may have changed the monetary transmission mechanism, first, by looking at the impact of financial variables in traditional VAR models and, second, by testing the impact of such variables in structural econometric models.

Evidence from VAR Models

Changes in monetary transmission associated with these changes in financial structure can be analyzed with VAR models, where a minimum structure is imposed and monetary shocks are identified as innovations to the interest rate equation. Standard VAR models used in studies of monetary transmission include a set of endogenous variables (output and prices) and an interest rate equation that captures a general monetary policy rule that affects the endogenous variables with a lag.3 Given Canada’s small open economy characteristics, the exchange rate is included in the model after the interest rate equation, together with a set of exogenous variables X.4

The benchmark VAR model has the representation

where

and y is quarterly GDP, p is the GDP deflator, R is the three-month T-bill rate,5 and S is the exchange rate. The vector of exogenous variables is given by

where yUS is U.S. GDP, RUS is the federal funds rate, and cp is an index of world commodity prices.

This benchmark VAR model is then extended with a block of financial variables, F, suggested by the credit channel literature. This includes quantity variables, aimed at capturing the role/existence of alternative sources of funding for the corporate and household sectors, as well as asset price variables, aimed to capture the role of collateral and the “external finance premium.”6

The VAR models are estimated in levels using quarterly data starting from 1971, the beginning of the floating exchange rate period, and ending in 2005. As in most VAR models of the monetary transmission mechanism, there is no explicit analysis of the longrun behavior of the economy. Doing the analysis in levels allows for implicit cointegrating relationships in the data, but cointegration is not explicitly imposed. Imposing cointegrating restrictions on a VAR in levels could increase efficiency in the estimation, but this would be at the cost of potential inconsistencies if the incorrect identifying restrictions are imposed. Since the monetary transmission mechanism is a short-run phenomenon, most researchers prefer to employ unrestricted VARs in levels to evaluate impulse responses over the short to medium run (Favero, 2001).

The dynamics of Canada’s output and prices are broadly similar to those of the United States, the European Union, the United Kingdom, and Japan, using similar benchmark VAR models.7 The impulse responses for the benchmark VAR for Canada for the full sample following a monetary shock are presented in the left-hand column of Figure 7.5. The decline in output after a contractionary monetary policy shock is somewhat smoother and more persistent in Canada, while the sluggish decline in prices (with an initial spike consistent with the so-called price puzzle) is similar to that of most other industrialized countries. The exchange rate appreciates for a period of about three years, but the results are not statistically significant for the full sample.

Figure 7.5.Impulse-Response Functions from Benchmark VAR

Source: IMF staff calculations.

Note: Solid black line shows impulse response. Other lines (dashed) show a two-standard-deviation confidence band.

The responses to a monetary shock during the full sample period are consistent with those of other industrialized countries, but the lack of significance and the fact that there were important regime changes8 suggest the possibility of a structural break in the statistical model in the late 1980s or early 1990s. Statistical tests for structural breaks at the dates when key changes to the Bank Act were implemented (1988:Q1 and 1993: Q2, as suggested by Calmes, 2004) confirm such breaks for both the benchmark and financial VARs.9

The instability of the VAR coefficients is confirmed with likelihood-ratio tests for all VAR models at the 5 percent confidence levels.

The second and third columns of Figure 7.5 show that the impulse responses in the first subsample (1971: Q1–1991:Q1) are more tightly estimated and show a statistically significant decline in output between the fifth and tenth quarters. Prices fall more gradually and persistently, while the exchange rate appreciates sharply on impact and returns to its baseline level afterward. However, the impulse responses for the second subsample (1991:Q1–2005:Q2) show a very different shape and are statistically insignificant.10

The extended VARs provide a tighter and improved characterization of the dynamics of macro variables after a monetary shock, especially for the first subsample. The variables added included both asset prices and quantities, and the ones that contributed to an improved characterization of the transmission of interest shocks to output and prices were business loans (see Figure 7.5) and asset prices (Figures 7.6 and 7.7). In particular, when each of these variables is added to the benchmark VAR, a statistically significant recession and a more tightly estimated response of the price level decline emerges for the first subsample, and the appreciation of the exchange rate after the increase in interest rates becomes statistically significant (Figure 7.8).

Figure 7.6.Impulse-Response Functions from VAR, Including Business Loans

Source: IMF staff calculations.

Note: Solid black line shows impulse response. Other lines (dashed) show a two-standard-deviation confidence band.

Figure 7.7.Impulse-Response Functions from VAR, Including Asset Prices

Source: IMF staff calculations.

Note: Solid black line shows impulse response. Other lines (dashed) show a two-standard-deviation confidence band.

Figure 7.8.Impulse-Response Functions from VAR, Including Asset Prices and Business Loans

Source: IMF staff calculations.

Note: Solid black line shows impulse response. Other lines (dashed) show a two-standard-deviation confidence band.

More important, the contribution of the interest rate shock to the variance of output fluctuations (as measured by the variance decompositions) increases markedly in the models with financial variables, suggesting that their addition contributes to a richer set of dynamic interactions and an improved characterization of the transmission mechanism. Monetary shocks explain close to 35–40 percent of the variance of output in the financial models, while they explain around 27 percent in the baseline model (see Roldos, 2006, Table 4).

The dynamics of output following a monetary shock seem to have changed earlier in the sample period than the dynamics of prices. The F-tests for individual equations in each VAR show a structural break for the output equations in all the models by 1988, while the price equation changes are more robust in the early 1990s (Roldos, 2006, Tables 1–3). This is consistent with changes in output being associated with the earlier changes in financial structure and with changes in prices being more closely associated with the changes in the monetary regime in the early 1990s.

The fact that responses to a monetary shock became weaker in the more recent subsample can be interpreted to reflect the fact that the systemic component of monetary policy (that is, the one captured by the monetary policy rule) has become more important with the increased transparency and other institutional improvements associated with the adoption of inflation targeting. This is consistent with a decline in the importance of monetary shocks—that is, the unexpected part of monetary policy captured by the VAR shocks. Indeed, the standard deviation of the monetary shocks in the second subsample is systematically smaller than in the first subsample. Similar conclusions can be drawn for the United States, in terms of both the instability of monetary VAR models and the increasing role of systematic monetary policy.11

In sum, both the benchmark and the VARs, which include financial variables, show a clear change in monetary transmission in the late 1980s or early 1990s. Since VARs are largely unrestricted, we cannot test specific hypothesis of what key factors are behind the changes in monetary transmission within this framework. For this, we now turn to specific tests of the role of financial variables in structural econometric models.

Evidence from Structural Models

Structural macroeconometric models used to analyze monetary policy issues generally do not explicitly incorporate financial sector features. However, Bean, Larsen, and Nikolov (2002) argue that a reduction in financial frictions associated with financial deepening and/or disintermediation would lower the persistence of moves in the output gap and would reduce the elasticity of the gap to the real interest rate (consistent with a reduction in the external finance premium and lower amplification of the initial monetary shock). Alternatively, it has been argued that bank lending is more relationship based and therefore less interest rate sensitive than market financing, suggesting that disinter-mediation would increase the elasticity of the gap to the interest rate.12 Thus, in the absence of clear-cut, testable implications from micro-founded models, this analysis estimates closed and open economy versions of an aggregate demand or IS equation and tests the sensitivity of the main coefficients to the evolution of financial variables.13

One simple closed-economy IS equation is that proposed by Rudebusch and Svensson (1999):

where y is the output gap and ρ is the annualized quarterly rate of inflation.14 Following Estrella (2002), the coefficients of the lagged gap and the real interest rate are allowed to vary with measures of financial innovation or disintermediation, and the significance of these variables is tested. Since the focus here is on the increase in the share of securities markets funding relative to bank lending, the coefficient α3 is made a function of the ratio of direct to indirect finance, DIF.15 To capture the two trends described previously (the decline in the share of bank lending to corporates and the growth of credit to households), two broad measures of financial disintermediation are considered, where DIF1 is the ratio of securities to business loans and DIF2 is the ratio of securities to total loans—to capture the increased lending to the household sector. The equations to be estimated are of the form

The estimation results confirm the changes in monetary transmission in the early 1990s, but do not seem to support the hypothesis that disintermediation is behind such changes. The estimates show that the interest rate elasticity of the output gap was significantly different from zero in the full sample, but also show that the significance is only for the more recent subsample (see Roldos, 2006, Tables 6 and 7, respectively). This stands in contrast to the results from the VAR models, which seem to suggest a loss in the effectiveness of monetary policy in the more recent sample period, and confirms the interpretation of a more important role for the systematic effects of monetary policy—given that this specification captures both the systematic and unexpected effects of interest rate changes.

There is no clear evidence from the closed-economy IS equation that the interest rate elasticity of the output gap has been affected by the shift toward market financing. The interest rate elasticity does not seem to depend on either measure of financial disintermediation.16

Although equation (4) is a useful simple benchmark, other more recent specifications of an aggregate IS equation may be more appropriate for Canada. These specifications are derived from micro-founded theoretical models and stress both forward-looking and open-economy aspects of aggregate demand.

Monetary policy models in the “New Keynesian” tradition are grounded in dynamic general equilibrium theory and capture the forward-looking behavior of optimizing firms and consumers. However, the empirical performance of these models is not satisfactory, and backward-looking elements have to be added to achieve a reasonable fit. Following Clarida, Galí, and Gertler (1999), a typical forward-looking IS equation with endogenous persistence can be specified as

where E is the expectations operator and the lagged real interest rate has been replaced by the current rate. However, the estimation results are not satisfactory when the expected output gap is replaced by the actual future gap. Although the future gap enters with a large and highly significant coefficient, the real interest rate loses significance and a high DW statistic suggest that an important degree of autocorrelation is not captured by this specification. The coefficients incorporating the ratio of direct to indirect finance DIF are also not statistically significant.17

Monetary policy models for the small open economy are isomorphic to the ones just discussed for the closed economy, except for the size of the parameters of the aggregate demand function. Clarida, Galí, and Gertler (2001) show that the introduction of a foreign country and foreign goods does not change the shape of the IS equation, except that the interest rate sensitivity of aggregate demand—the parameter α2 in the previous equations—depends now on the degree of openness or the share of foreign goods in total consumption, a slow-moving variable.

Despite the fact that the real exchange rate does not appear as an independent variable in the micro-funded models of aggregate demand, several analysts and central banks include this variable in the IS equation. Moreover, popular open economy models, such as the one in McCallum and Nelson (1999a), include shocks to foreign output in the IS equation. Thus, an open economy IS equation of this form

was estimated, where z is the real exchange rate gap and y* is the U.S. GDP gap.18 The real exchange rate gap is the difference between the actual real exchange rate and a Hodrick-Prescott-filtered version of the same variable. The resulting real exchange rate gap measure is qualitatively similar to the measure presented in Figure 2 in Berg, Laxton, and Karam (2006), which imposes uncovered interest rate parity and uses a flexible combination of backward- and forward-looking elements to calibrate an equation similar to (7).

Estimates of the open economy IS equation provide evidence that disintermediation has contributed to the changes in monetary transmission experienced in Canada. In particular, the interest rate elasticity of aggregate demand is not statistically different from zero for the full sample period under study (1971– 2005, see Table 7.1), but the elasticity becomes significant when it is estimated as a linear function of the ratio of direct to indirect finance as in equation (5).19 This suggests that the trends of intermediation (in the 1970s) and disintermediation (in the 1990s) might have cancelled out when they were omitted in the initial specification. Moreover, the coefficients on DIF1 and DIF2 become significant in the second half of the sample and yield relatively larger estimates of the interest elasticity (respectively, −0.46 and −0.48, for the average sample values of DIF1 and DIF2; see Table 7.2). This suggests that the responsiveness of aggregate demand to monetary policy actions has become stronger with the process of financial disintermediation during the 1990s.

Table 7.1.Estimates of Open Economy IS Equation (1971:Q1–2005:Q2)
Open Economy

IS Equation
Model

with DIF1
Model

with DIF2
α0−0.0960.137−0.054
(0.837)(0.768)(0.906)
α11.0210.9720.979
(0.000)(0.000)(0.000)
α2−0.252−0.229−0.229
(0.001)(0.003)(0.003)
α30−0.0720.8740.658
(0.312)(0.022)(0.031)
α31−0.505−1.191
(0.012)(0.014)
α4−0.027−0.018−0.019
(0.628)(0.747)(0.737)
α50.4400.6280.602
(0.000)(0.000)(0.000)
R20.8380.8450.845
DW1.791.761.78
Source: Author’s calculations.Notes: DIF1 is the ratio of direct to indirect finance for the corporate sector; DIF2 is the ratio of direct finance to total lending—including the household sector.p-values are in parentheses.
Table 7.2.Estimates of Open Economy IS Equation (Sample Break in 1988:Q1)
Open Economy IS EquationModel with D1F1Model with D1F2
(1971:1–1988:1)(1988:1–2005:2)(1971:1–1988:1)(1988:1–2005:2)(1971:1–1988:1)(1988:1–2005:2)
α0−1.5670.337−1.4951.209−1.2921.346
(0.058)(0.428)(0.072)(0.043)(0.142)(0.025)
α10.7471.3030.7401.1720.7341.143
(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)
α2−0.204–0.427−0.187−0.333−0.192−0.313
(0.057)(0.000)(0.087)(0.005)(0.075)(0.008)
α300.201−0.17−0.9781.672−0.5792.13
(0.115)(0.029)(0.475)(0.070)(0.519)(0.030)
α310.653−0.9411.333−3.571
(0.387)(0.046)(0.381)(0.019)
α40.026−0.0250.032−0.1040.039−0.112
(0.791)(0.697)(0.738)(0.165)(0.687)(0.125)
α51.0250.3750.9560.5940.9990.626
(0.000)(0.017)(0.000)(0.002)(0.000)(0.001)
R20.7710.9430.7730.9470.7730.948
DW1.801.931.821.821.801.80
Source: Author’s calculations.Notes: DIF1 is the ratio of direct to indirect finance for the corporate sector; DIF2 is the ratio of direct finance to total lending—including the household sector.p-values are in parentheses.

Conclusions and Policy Implications

This analysis shows that monetary transmission in Canada has changed markedly since the late 1980s and also provides evidence that financial disintermediation has contributed to these changes. Estimated VAR models show a clear break in monetary transmission beginning in 1988, after changes in financial sector regulation initiated the process of financial disintermediation. Although the inclusion of financial variables in VAR models improves the characterization of monetary transmission in the period before the structural break, the models suggest a decrease in the effectiveness of monetary policy during the 1990s. However, there is evidence suggesting that this may be related to the fact that VAR models capture the impact of unexpected monetary shocks, while the systemic component of monetary policy—which is not captured in the impulse responses—has likely become more important with the improvements in the monetary framework during the 1990s. As in other industrialized countries, changes in monetary policy, the nature of global shocks, and other structural changes probably also played a significant role in monetary transmission.20

The process of disintermediation has contributed to changes in the sensitivity of aggregate demand to real interest rates, a key parameter in the transmission of monetary policy to the real economy. Estimates of the interest rate elasticity of aggregate demand in IS equations increase during the 1990s, confirming the interpretation that the systemic component of monetary policy has become more relevant recently. Moreover, changes in the ratio of direct to indirect finance, a measure of disintermediation, help explain the changes in the interest rate elasticity and suggest an increase in the effectiveness of monetary policy associated with a larger use of market-based sources of finance during the 1990s. This could be attributed to the lower interest rate sensitivity of relationship-based bank lending compared to the more price-sensitive direct or market funding.

Monetary policy appears to have become more effective during the 1990s, when measured through the average impact of interest rate changes on the output gap or, alternatively, on aggregate demand. However, this increased effectiveness may be undermined by more recent increases in household borrowing and the relative decline in the issuance of corporate securities, the ratio of direct to indirect finance, which has been lowering since 2002. Although the increasing role of the household sector may change monetary transmission in ways not captured in the simple models considered here, the analysis of monetary policy could benefit from a more explicit consideration of the evolving role of financial markets and intermediaries.

For a thorough account of these and other trends, see Freedman and Engert (2003) and Calmes (2004).

This is the standard recursivity assumption; see Christiano, Eichenbaum, and Evans (1999) and Favero (2001).

The exogenous variables included are U.S. GDP, U.S. federal funds rate, and an index of world commodity prices.

Although the overnight rate is the Bank of Canada monetary policy instrument, which is the best variable to summarize the monetary policy stance (Fung and Yuan, 1999), it is rather unstable in the first part of the sample. Thus, we use the T-bill rate, which is highly correlated with the overnight rate and is also the variable used in several European Union studies that will serve as comparisons to the Canada case.

The variables included were total loans to businesses and households; securities (bond, equities, and commercial paper); and ratios that micro studies have found relevant for the credit channel (such as the ratio of commercial paper to business loans; see Kashyap and Stein, 1994). The price variables included spreads on loans, commercial paper, and bonds, as well as stock and housing pr ices (and an aggregate asset price index, with equal weights of both of them).

Changes occurred in both financial regulation and in monetary policy; on the latter, see Atoyan (2004).

See the last line in Tables 1 and 2 in Roldos (2006). The relatively small sample does not provide the degrees of freedom necessary to perform continuous break tests and let the data show the true break point. Tests for an intermediate date, 1991:Q1, reported in Table 3 in Roldos (2006), yield results that are qualitatively similar to those of the second break test.

A similar pattern arises for the different components of aggregate demand: private consumption falls smoothly but persistently between the fourth and tenth quarters; investment falls three times as much as consumption; and residential investment falls more than total investment. In the second subsample, residential investment falls significantly during the first year only (despite the mild response in GDP), and several of the results are statistically insignificant.

Bank loans are implicit contracts that allow for more flexibility in renegotiation and risk sharing, features that are not necessarily reflected in market prices or interest rates (Allen and Gale, 2000).

Typical New Keynesian models of monetary policy also include a Phillips curve (or aggregate supply) and interest rate equations (Clarida, Galí, and Gertler, 1999).

The output gap is defined as the ratio of actual GDP to a Hodrick-Prescott-filtered version of the same series; the inflation rate is the same period change in the GDP deflator.

Estrella (2002) makes the coefficient α3 a function of the degree of securitization of mortgage loans only. For the United States, he finds that the elasticity of the gap to the real interest rate falls as the degree of mortgage securitization increases, and he interprets the result as a decline in the efficacy of monetary policy. The coefficients on the output lags do not seem to be affected by the disintermediation variables.

For the average values of the variables DIF1 and DIF2, the interest elasticity coefficients become −0.33 and −0.46, respectively. However, for their current values, the coefficients are not very different from zero. See Roldos (2006), Table 6.

Results are available upon request.

Since the forward-looking component of the output gap generates a high degree of unexplained autocorrelation and a nonsignificant interest rate elasticity, a version with two lags of the Canadian output gap was estimated. The U.S. GDP measure of potential output is a Hodrick-Prescott filter of GDP until 1980, and staff estimates afterwards.

When calculated using the average sample values of DIF1 and DIF2, both elasticities are, respectively, −0.15 and −0.09.

Stock and Watson (2003) estimate that for the United States, changes in policies account for around one-quarter of the reduction in volatility of the major macroeconomic aggregates.

    Other Resources Citing This Publication