Policy Uncertainty in Japan
  • 1 0000000404811396https://isni.org/isni/0000000404811396International Monetary Fund
  • | 2 0000000404811396https://isni.org/isni/0000000404811396International Monetary Fund

We develop new economic policy uncertainty (EPU) indices for Japan from January 1987 onwards building on the approach of Baker, Bloom and Davis (2016). Each index reflects the frequency of newspaper articles that contain certain terms pertaining to the economy, policy matters and uncertainty. Our overall EPU index co-varies positively with implied volatilities for Japanese equities, exchange rates and interest rates and with a survey-based measure of political uncertainty. The EPU index rises around contested national elections and major leadership transitions in Japan, during the Asian Financial Crisis and in reaction to the Lehman Brothers failure, U.S. debt downgrade in 2011, Brexit referendum, and Japan’s recent decision to defer a consumption tax hike. Our uncertainty indices for fiscal, monetary, trade and exchange rate policy co-vary positively but also display distinct dynamics. VAR models imply that upward EPU innovations foreshadow deteriorations in Japan’s macroeconomic performance, as reflected by impulse response functions for investment, employment and output. Our study adds to evidence that credible policy plans and strong policy frameworks can favorably influence macroeconomic performance by, in part, reducing policy uncertainty.

Abstract

We develop new economic policy uncertainty (EPU) indices for Japan from January 1987 onwards building on the approach of Baker, Bloom and Davis (2016). Each index reflects the frequency of newspaper articles that contain certain terms pertaining to the economy, policy matters and uncertainty. Our overall EPU index co-varies positively with implied volatilities for Japanese equities, exchange rates and interest rates and with a survey-based measure of political uncertainty. The EPU index rises around contested national elections and major leadership transitions in Japan, during the Asian Financial Crisis and in reaction to the Lehman Brothers failure, U.S. debt downgrade in 2011, Brexit referendum, and Japan’s recent decision to defer a consumption tax hike. Our uncertainty indices for fiscal, monetary, trade and exchange rate policy co-vary positively but also display distinct dynamics. VAR models imply that upward EPU innovations foreshadow deteriorations in Japan’s macroeconomic performance, as reflected by impulse response functions for investment, employment and output. Our study adds to evidence that credible policy plans and strong policy frameworks can favorably influence macroeconomic performance by, in part, reducing policy uncertainty.

I. Introduction

Efforts to reinvigorate Japan’s economy have proved challenging. Despite significant policy accommodation, growth over the past two decades has been weak, the share of non-regular employment has increased, wages have been stagnant, and inflation expectations lie below the Bank of Japan’s inflation target. Observers cite demographic headwinds, other structural factors, the zero lower bound, external shocks, and policy mistakes as reasons for Japan’s chronically weak economic performance. We focus on another, overlapping factor: uncertainty about policy and its effects.

Previous studies and policymaker remarks suggest that uncertainty about U.S. and European policies contributed to a steep economic decline in 2008–09 and slow recoveries thereafter.2 Policy uncertainty has returned to the forefront amid concerns over the European immigration crisis, the Brexit referendum, a failed coup in Turkey, the U.S. election outcome, China’s tightening capital controls, presidential removals in Brazil and South Korea, and populist political forces in several countries.3 According to an aggregation of newspaper-based indices for 16 countries in Davis (2016), global economic policy uncertainty in 2016 exceeds even the high levels reached in 2008 Q4 and 2009 Q1.

In Japan, an unsustainable fiscal trajectory, constraints on monetary policy, and weak growth present major challenges that intensify policy uncertainty. Shinzo Abe’s election as Prime Minister in December 2012 and his economic reform initiatives (“Abenomics”) marked an important milestone and a clearer policy direction after six prime ministers in six years. There was some acceleration in growth during this period as well as some success in boosting inflation and progress with structural reforms. However, maintaining confidence in Abenomics has proved difficult. Fiscal policy targets are no longer seen as credible, contributing to policy uncertainty. A consumption tax hike initially scheduled for 2015 was postponed twice, first to 2017 and then to 2019. Frequent use of supplementary budgets adds to uncertainty about the near-term fiscal stance. New monetary easing measures and technical changes to the monetary policy framework also contributed to uncertainty. Structural reforms related to labor markets, immigration and trade policy could improve growth prospects, but whether and how Japan will achieve these reforms is highly uncertain.4

Against this backdrop, we take up three questions: How has policy uncertainty moved over time in Japan? Which policy areas account for the largest share of policy uncertainty and its movements? What do changes in policy-related uncertainty portend for Japan’s economic performance? To address these questions, we construct several newspaper-based policy uncertainty measures for Japan following the methods in Baker et al. (2016). We interpret these measures as proxies for policy-related uncertainty, as perceived by households and businesses. We relate our measures to other uncertainty measures, examine their behavior over time, and consider their dynamic relationship to aggregate economic performance.

Our measures aim to capture uncertainty about who will make economically relevant policy decisions, what policy actions will be undertaken and when, and the economic effects of policy actions (or inaction). To construct our overall measure of economic policy uncertainty (EPU), we count articles in four major Japanese newspapers (Yomiuri, Asahi, Mainichi and Nikkei) that contain at least one term in each of three categories: (E) ‘economic’ or ‘economy’; (P) ‘tax,’ ‘government spending’, ‘regulation,’ ‘central bank’ or certain other policy-related terms; and (U) ‘uncertain’ or ‘uncertainty’. We scale the EPU counts by the number of articles in the same newspaper and month, standardize each paper’s series of scaled counts to the same variability over time, adjust for seasonality, and then average across papers by month to obtain our EPU index. We also construct uncertainty indices for monetary policy, fiscal policy, trade policy and exchange rate policy. To do so, we specify additional criteria for those articles that contain our triple of terms about the economy, policy and uncertainty. All of our measures are monthly from 1987 to the present, and we plan monthly updates.

Our overall EPU index co-varies positively with implied volatilities for Japanese equities, exchange rates and interest rates and with Ito’s (2016) survey-based measure of political uncertainty in Japan. Our index peaks during the Asian Financial Crisis and in reaction to the failure of Lehman Brothers, the U.S. debt-ceiling fight in 2011, the Brexit referendum and the recent deferral of a hike in the consumption tax rate. The index also shows a clear tendency to rise around contested national elections and major leadership transitions. It displays moderately countercyclical fluctuations,5 perhaps because policymakers are more inclined to experiment with new policies in bad times (Pastor and Veronesi, 2013).

Uncertainty indices for fiscal, monetary, trade and exchange rate policy correlate positively with one another, while also displaying distinct and intuitive dynamics. For example, implied interest rate volatility correlates more highly with our monetary policy uncertainty index than with our fiscal policy uncertainty index. In contrast, Ito’s (2016) measure of political uncertainty, which weighs the approval ratings of ruling and opposition parties, correlates more highly with fiscal policy uncertainty. Among all articles that satisfy our E, P and U criteria, 57 percent reference fiscal policy matters, 27 percent reference monetary policy, 8 percent reference trade policy, and only 3 percent reference exchange rate policy. This finding strongly suggests that fiscal matters are the most important source of policy uncertainty in Japan, at least in the perception of journalists and their editors and, presumably, typical newspaper readers as well.

Our EPU measures have predictive power for Japan’s economic performance conditional on standard measures of economic activity and uncertainty. In particular, vector autoregressive (VAR) specifications imply that upward EPU innovations foreshadow deteriorations in Japan’s macroeconomic performance, as reflected in impulse response functions for investment, employment and output. We also find a significant effect of global economic policy uncertainty on Japan’s economic performance when we use the Global EPU index of Davis (2016). These VAR results do not prove a causal effect of policy uncertainty on economic performance, but they show that our EPU index contains useful information not captured by other forward-looking indicators. Upward innovations to our EPU index for Japan also foreshadows a larger decline in macroeconomic aggregates than innovations to the Japan EPU index in Baker et al. (2016), suggesting that our efforts to improve the index deliver a better measure and stronger results in downstream econometric work.

II. Related Literature

Compared to the Japan EPU index in Baker et al. (2016), we expand coverage from two to four major newspapers, and we deploy a better term set that reflects our auditing efforts and our expertise in Japanese economic policy. Unlike Baker et al. (2016), we also develop indices for several policy categories, which we see as helpful in diagnosing the proximate sources of policy uncertainty and potentially quite useful in analyzing policy uncertainty effects on industry- and firm-level outcomes. Alexopoulos and Cohen (2015), Azzimonti (2015), Hassan et al. (2016), Hlatshwayo and Saxegaard (2016) and Husted, Rogers and Sun (2016a) also use text analysis to quantify policy uncertainty and related concepts. Other approaches to the quantification of policy uncertainty include Ito’s (2016) survey-based measure for Japan, the country-level volatility of government consumption shocks in Fátas and Mihov (2013), the use of multivariate GARCH models in Grier and Perry (2000) and Vitek (2002), and time-varying measures of fiscal policy uncertainty derived from an estimated New Keynesian model in Fernandez-Villaverde et al. (2015).

Theoretical work identifies several channels through which uncertainty can affect economic outcomes. First, heightened uncertainty provides an incentive to delay or forego investments that are costly to reverse (Bernanke, 1983, McDonald and Siegel, 1986, Dixit and Pindyck, 1994, Bloom et al., 2007 and Bloom, 2009). High uncertainty also encourages households to postpone costly-to-reverse purchases of durable goods (Eberly, 1994). Second, search frictions in labor markets and fixed costs of hiring and firing can retard hiring or induce firms to adjust on flexible margins such as part-time employment (Schaal, 2015, and Valetta and Bengali, 2013). Leduc and Liu (2016) show how nominal rigidities can interact with labor market search frictions to amplify the negative effects of uncertainty in DSGE models. Related to these channels, uncertainty can slow the growth of productivity and output by discouraging the reallocation of capital and labor inputs (Bloom et al., 2012). Third, uncertainty can depress investment by raising risk premiums, as stressed by several models with financial frictions (Arellano et al., 2010, Christiano et al., 2014, and Gilchrist et al., 2014). Fourth, greater uncertainty raises precautionary savings by households, which can reduce output in the presence of nominal rigidities, especially under constraints on monetary policy (Johansen, 2014, and Fernandez-Villaverde et al., 2015). Fiscal policy uncertainty also reduces output by intensifying monopoly pricing distortions in the model of Fernandez-Villaverde et al. Fifth, uncertainty can stimulate investment by increasing the value of growth options (Paddock et al., 1988, and Bar-Ilan and Strange, 1996). See Bloom (2014) for a fuller discussion of how uncertainty affects economic activity.6

Several recent empirical studies investigate the effects of policy uncertainty on economic outcomes in Japan and elsewhere. Ito (2016) finds negative effects of policy uncertainty on employment and expenditures for consumer durables. Morikawa (2013, 2016) provides survey-based evidence of how Japanese companies perceive the relevance of policy uncertainty. Morikawa (2010), Ono and Sullivan (2013) and Matsuura (2013) find a greater use of non-regular workers at firms with greater sales growth volatility. Beyond the Japanese context, Durnev (2012), Julio and Yook (2012, 2016), Giavazzi and McMahon (2012) and Kelly, Pastor and Veronesi (2016) investigate the effects of election-related uncertainty on corporate investment, international capital flows, precautionary savings, and stock price volatility. Handley and Limao (2015) develop evidence that lower uncertainty about trade policy stimulates investment in export capacity. Gulen and Ion (2016) find negative effects of policy uncertainty on corporate investment using the Baker et al. (2016) EPU measure for the United States. Similarly, Baker et al. (2016) find larger negative effects of their newspaper-based EPU measures on investment rates and employment growth, and larger positive effects on stock price volatility, for firms with greater exposure to policy risks. Using the EPU index for India in Baker et al., Anand and Tulin (2014) find negative effects of policy uncertainty on firm-level investment flows, with stronger effects on new projects than ongoing ones.

Another branch of the literature investigates the dynamic relationship of policy uncertainty, or economic uncertainty more broadly, to macroeconomic performance. Examples include Stock and Watson (2012), Colombo (2013), International Monetary Fund (2013), Jurado et al. (2015), Ludvigson et al. (2015), Baker et al. (2016) and Leduc and Liu (2016). These studies find that higher (policy) uncertainty foreshadows a deterioration in macroeconomic performance, broadly in line with our evidence for Japan. Romer (1990) marshals evidence that the 1929 stock market crash triggered a sharp rise in income uncertainty that led households to forego purchases of consumer durables, accentuating the collapse of aggregate demand at the onset of the U.S. Great Depression. Evidence in Constantinescu et al. (2017) suggests that high policy uncertainty depresses international trade in goods and services.

In summary, a variety of studies find evidence that high (policy) uncertainty undermines economic performance by leading firms to forego investments and new hires, by slowing productivity-enhancing factor reallocation, and by depressing expenditures on consumer durables. This evidence points to a positive payoff in the form of stronger macroeconomic performance if policymakers can deliver greater predictability in the policy environment. For Japan, possibilities in this regard include a concrete and credible medium-term fiscal plan, clear follow through on structural reform plans, and a stronger communications framework at the Bank of Japan. A smaller literature finds that greater uncertainty causes households and firms to become less responsive on the margin to cuts in interest rates and taxes, in line with predictions of real options theory. See Bertola et al. (2005), Bloom et al. (2007), Bloom (2009), Aastveit et al. (2013) and Vavra (2014). These studies suggest that a stronger policy framework also increases the potency of countercyclical stabilization policies.

III. Measuring Economic Policy Uncertainty in Japan

Following Baker et al. (2016), we use frequency counts of newspaper articles to construct our EPU indices. As a first step, we obtain raw monthly EPU article counts for Yomiuri, Asahi, Mainichi and Nikkei from January 1987 onwards. Our primary data sources are Kikuzo II, MAISAKU, Nikkei Telecom, and Yomidas Rekishikan. To meet our EPU criteria, an article must contain at least one term in the “economy” (E), “policy” (P) and “uncertainty” (U) categories listed in Table 1. The E and U categories are straightforward. For the P category, we sought to cover major policymaking institutions (e.g., “lower” and “upper house”, “Diet”, “central bank” and “Prime Minister”) and major policy areas (e.g., “taxes”, “government deficit”, “government debt”, “(de)regulation” and “structural reform”). We conducted a series of small-scale audits and other investigations to help select and refine the E, P and U term sets, as detailed in the appendix.

Table 1.

Term Sets for the Overall Japan EPU Index

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In a second step, we scale the raw EPU counts by the total number of articles in the same newspaper and month to obtain a relative EPU frequency count. Scaling in this manner adjusts for differences in article volume across newspapers and volume changes over time. Third, we standardize each newspaper’s relative EPU counts to unit standard deviation from 1987 to 2015. Fourth, we seasonally adjust the resulting newspaper-level series in view of the pronounced and distinctive seasonal pattern at certain papers. The appendix provides more information about seasonality and explains how we performed the adjustment. Fifth, after the scaling, standardization and seasonal adjustment steps, we average the resulting series across the four papers by month to obtain our overall monthly Japan EPU index. The third, fourth and fifth steps ensure that each newspaper receives (roughly) equal weight in determining the behavior of the overall index, despite differences across papers in the share and variability of articles about business and economics. Finally, we multiplicatively normalize the four-paper average EPU series to a mean of 100 from 1987 to 2015.

To accurately mirror variation in policy-related uncertainty over time, our EPU index must satisfy two requirements. First, the E, P and U criteria must yield counts that move in line with actual newspaper coverage of economic policy uncertainty. We relied on several small-scale audits to evaluate and refine our choice of terms, with an eye towards minimizing classification errors. See the appendix for details. Second, newspaper coverage must reflect movements in policy uncertainty. To address this requirement, we compared our newspaper-based EPU measures to other measures of economic and political uncertainty for Japan. We also conducted a descriptive assessment of the key economic and policy developments associated with heightened levels of policy uncertainty according to our index. We report the results of these investigations below.

The Japan Economic Policy Uncertainty Index

Figure 1 plots our overall EPU index for Japan from January 1987 to March 2017. The index peaks during the Asian Financial Crisis and in reaction to the “Twisted Diet” election outcome in 1998, 7 the introduction of Quantitative Easing in 2001, the Takenaka Plan for tackling longstanding problems with non-performing loans at Japanese banks, the Lehman Brothers failure in September 2008, and the Greek Crisis and Twisted Diet election outcome in 2010, and the U.S. debt-ceiling fight in summer 2011. The Japan EPU index is moderately countercyclical, but it also displays many strong movements not tied directly to cyclical conditions. In April 2001, Junichiro Koizumi became Prime Minister, a position he held until 2006, making him one of the longest serving Prime Ministers in Japan’s history. The EPU index drifts down during this period of political continuity and reaches some of its lowest values in our sample period. The index also exhibits a period of gradual decline starting in 2013, coinciding with the launch of Abenomics and an improvement in confidence indicators.8 Since 2015, policy uncertainty has risen again amid concerns about developments in China, a new negative interest rate policy, the Brexit referendum, consumption tax hike delays and elections in the US.

Figure 1.
Figure 1.

Japan Economic Policy Uncertainty Index (1987M1–2017M3)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Authors’ calculations.A, October 1987: Black Monday. Takeshita becomes next LDP President. Budget conflicts between President Reagan and Congress. FX intervention. B, March 1995: Bailout plans for two Shinkin banks in Tokyo face objection at metropolitan congress. Yen surges despite FX intervention. Debate about policy rate cut. C, November-December 1997: Asian Financial Crisis, successive failures of banks and securities firms, and policy debates about fiscal consolidation. D, July-August 1998: LDP’s defeat in Upper House election yields Twisted Diet. Russian crisis. E, June 2000: Lower House election. F, February-March 2001: Political confusion over PM Mori’s resignation. Introduction of Quantitative Easing. G, July 2001: Upper House election. H, October 2002: Takenaka’s plan to tackle non-performing bank loans. Introduction of Financial Revitalization Program. Stimulus debate. Expansion of QE. I, March 2008: DPJ rejects BOJ Governor nominations. J, September-October 2008: Lehman Brothers failure. BOJ cuts policy rate. Stimulus debate. K, February 2009: Concerns over delay in passing US stimulus package. “Buy American” provisions in Congress. L, May-June 2010: Greek crisis. PM Hatoyama’s resignation. Inauguration of PM Kan’s cabinet. M, August 2011: U.S. debt downgrade. Concerns over European debt crisis. Enhancement of monetary easing. Japan FX intervention. PM Kan resigns. N, June 2012: Greek parliamentary re-election. Concerns over Spain’s financial system. Tri-party agreement on taxes and social security. O, January-February 2016: Introduction of negative interest rates. P, May-June 2016: Consumption tax hike delay. Brexit. Q, November 2016-January 2017: US Presidential election, worries about ratification of TPP in the US.Note: Shaded areas indicate recession periods.

Figure A.1 compares our overall Japan EPU index to the one in Baker et al. (2016). The two indices are highly correlated, as expected given the overlap in newspapers and term sets, but there are differences. For example, the Baker et al. index displays higher volatility during the late 1980s and early 1990s. Our Japan EPU index shows a more persistent rise during the Asian Financial Crisis. It also shows larger spikes in reaction to the Lehman Brothers failure and the US debt downgrade. As mentioned earlier, our index reflects articles in four rather than two Japanese newspapers – including the Nikkei, which specializes in business and economics. Doubling the number of papers lets us average out more of the idiosyncratic, newspaper-level noise. Unlike Baker et al. (2016), we also adjust for seasonality. Finally, our expanded and refined set of terms also leads to differences between the two indices.

Uncertainty Indices for Policy Categories

We also constructed uncertainty indices for fiscal, monetary, trade and exchange rate policy. To obtain raw frequency counts for these indices, we flagged articles that meet the E, P and U criteria, as before, and that contain one or more of the terms listed in Table 2 for particular policy categories. We then followed the same sequence of steps as for the overall EPU index. Here as well, we relied on informal audits and other investigations to inform our choice of term sets in Table 2. See the appendix for details.

Table 2.

Term Sets for Policy Category Uncertainty Indices

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Figures 2 and 3 display our Japan uncertainty indices for fiscal and monetary policy.9 Their movements broadly conform to our priors – rising around major economic and political events and policy announcements. The two indices correlate at 0.68. Both indices exhibit large jumps during the Asian financial crisis and in reaction to the Brexit referendum.10

Figure 2.
Figure 2.

Fiscal Policy Uncertainty Index (1987M1–2017M3)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Authors’ calculations.A: October 1987. Black Monday. Takeshita becomes next LDP President. Budget conflicts between President Reagan and Congress. B: November-December 1997. Asian Financial Crisis and policy debates about fiscal consolidation. C: July 1998. LDP’s defeat at Upper House election yields Twisted Diet. D: May 1999. Political conflict regarding pension reform and long-term care insurance system. E: June 2000. Lower House election. F: February-March 2001. Political confusion over PM Mori’s resignation. G: July 2001. Upper House Election. H: October 2002. Debate on economic stimulus package. I: August 2005. Political conflict over the postal privatization bills. PM Koizumi dissolves the lower house. J: January 2008. Stimulus package conflicts between President Bush and Congress. Political conflict regarding extension of provisional gasoline and other taxes in the Diet. K: October 2008. Lehman Brothers failure and stimulus debate. L: August 2009. Lower House election, DPJ takes office. M: May-June 2010. Greek crisis. PM Hatoyama’s resignation. Inauguration of PM Kan’s cabinet. N: August 2011. U.S. debt downgrade and concerns about European debt crisis. PM Kan’s resignation and DPJ’s leadership election. O: June 2012. Sovereign debt problems in Greece and Spain. Tri-party agreement on tax and social security reform. P: May-June 2016. Consumption tax hike delay and Brexit.Note: Shaded areas indicate recession periods.
Figure 3.
Figure 3.

Monetary Policy Uncertainty Index (1987M1–2017M3)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Authors’ calculations.A: October 1987. Black Monday. FX intervention. B: July 1992. BOJ cuts policy rate. C: March 1995. Japan’s banking crisis. Coordinated FX intervention. Debate about policy rate cut. D: November 1997. Asian Financial Crisis. Special BOJ loans to stabilize financial system after bankruptcy of Hokkaido Takushoku Bank and Yamaichi Securities. E: March 1998. BOJ Governor Matsushita resigns. F: October 1998. Debate on further monetary easing amid mounting concern over the financial system. G: March 2001. Introduction of QE. H: February 2002. Debate on expansion of QE. I: September-October 2002. Debate on expansion of QE. J: May 2003. Concerns over the spread of SARS epidemic. Expansion of QE. BOJ’s provision of special loans to Resona Bank. K: August 2007. Disarray in global financial markets with the outbreak of U.S. subprime loan crisis. Injection of liquidity by central banks. Debate about policy rate cut in Japan and the US. L: March 2008. Concerns over vacancy of BOJ Governor. M: October 2008. Lehman Brothers failure. BOJ cuts policy rate. N: August 2010. Debate on QE enhancement amid sharp yen appreciation. O: August 2011. QE enhancement and the BOJ’s unilateral FX intervention. P: June 2013. Concerns over FED QE tapering. Q: November 2014. Debate on the BOJ’s QE program under PM Abe’s decision to delay the consumption tax hike planned for October 2015. R: January-February 2016. Introduction of negative interest rates. S: May-July 2016. Debate on FX intervention amid surge in yen. Brexit. Enhancement of monetary easing.Note: Shaded areas indicate recession periods.

They also display distinct movements. For example, the fiscal policy uncertainty index responds (more) to contested elections, Twisted Diet episodes, political confusion surrounding Prime Minister Mori’s resignation, debates over stimulus packages in 2002 and 2008, and the ruling DPJ party’s talks with the opposition LDP and Komeito parties in 2012 about social security and tax bills. The fiscal policy uncertainty index also picks up major external developments such as the US government debt downgrade and the European debt crisis. In contrast, the monetary policy uncertainty index spikes around the introduction of Quantitative Easing (QE) in 2001, uncertainty over its expansion in 2001–02 and 2010–11, and the introduction of negative rates in 2016. It also peaks in March 2008 amid concerns surrounding a vacancy in the Bank of Japan’s Governor position, which arose because the ruling parties could not secure Diet approval for the proposed appointee.

Figures 4 and 5 compare our fiscal and monetary policy uncertainty indices with their US counterparts in Baker et al. (2016).11 They correlate at about 0.3 for both fiscal and monetary policy. Fiscal policy uncertainty was higher and more volatile in the U.S. during the late 1980s and early 1990s. The reverse pattern held during the Asian Financial Crisis. In recent years, U.S. fiscal policy uncertainty has been relatively muted, except for a jump in response to the November 2016 elections. In contrast, Japan has experienced elevated levels of fiscal policy uncertainty, partly due to uncertainty surrounding consumption tax hikes. Monetary policy uncertainty indices rose for both countries around the stock market crash of 1987, the Asian Financial Crisis and in the early 2000s. They fell for both during the mid-to-late 2000s and rose again during the global financial crisis of 2008-09. The Japan monetary policy uncertainty index has been highly elevated since the introduction of negative interest rates in late January 2016, while the U.S. index has remained at low levels except for a temporary spike in reaction to the Brexit referendum. See Cecchetti and Schoenholtz (2016) for a fuller discussion of recent policy shifts by the Bank of Japan.

Figure 4.
Figure 4.

Fiscal Policy Uncertainty Indices for Japan and the United States (1987M1–2016M12)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Baker et al. (2016) and authors’ calculations.
Figure 5.
Figure 5.

Monetary Policy Uncertainty Indices for Japan and the United States (1987M1–2016M12)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Baker et al. (2016) and authors’ calculations.

Figure 6 exhibits two periods of elevated trade policy uncertainty: the late 1980s and early 1990s, and the years since 2011. The first period reflects pressure on Japan from major trading partners to reduce import barriers. Our index responds to several bilateral talks between Japan and the US in this period. For example, the US named Japan an unfair trading partner under the “Super 301” provision of the Omnibus Trade and Competitiveness Act of 1988. Negotiations began on certain products under threat of retaliation against Japanese exports to the United States. The US also pushed for quantitative targets for imports in semiconductors, autos and auto parts in this period. Since 2011, developments related to the Trans Pacific Partnership (TPP) loom large. Sources of trade policy uncertainty include whether Japan would join the talks, whether an agreement could be reached with all parties, and whether the agreement would be ratified. More recently, the Brexit referendum outcome in the United Kingdom and the US elections triggered major spikes due to uncertainty about Japan’s future trade arrangements with these countries.

Figure 6.
Figure 6.

Trade Policy Uncertainty Index (1987M1–2017M3)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Authors’ calculations.A: March 1987. US sanctions on Japanese semi-conductors. B: January 1988. Deliberation on Omnibus trade bill in US Congress. C: December 1993. GATT Uruguay Round of multilateral trade talks. Partial opening of rice market and tariff cut on imported beef. D: March 1994. Revival of Super 301 provision in US Omnibus Trade Act of 1988. E: September 1997. Asian Financial Crisis. F: February 2009. Deliberation on “Buy American” provision in US Congress. G: November 2010. Conflict over participation in TPP talks with the ruling coalition. PM Kan announces Japan will begin consultations on participating in TPP talks. H: January 2011. PM Kan’s statement on TPP. Cabinet reshuffling. I: November 2011. Political conflicts over Japan’s participation in TPP talks. J: November-December 2012. Uncertainty over Japan’s participation in TPP talks. PM Noda decides not to announce participation and dissolves the Lower House. LDP returns to power, intensifying uncertainty around Japan’s participation in TPP. K: March 2013. PM Abe announces Japan’s participation in TPP talks. L: July 2013. Upper House election. M: October 2013. TPP summit ends without reaching broad agreement. N: April 2014. Uncertainty about whether Japan and the US would reach agreement on TPP, and concerns whether US Congress would grant President Obama trade promotion authority. O: October 2015. Uncertainty over TPP ratification in Japan, Canada and the US despite broad agreement at ministerial meeting earlier in month, P: January 2016. Uncertainty over TPP ratification by US amid upcoming presidential elections. Resignation of Minister Amari in charge of TPP negotiations due to corruption allegations. Q: June 2016. Brexit. R: November 2016-January 2017. US Presidential election, worries about ratification of TPP in the US.Note: Shaded areas indicate recession periods.

Figure 7 shows our uncertainty index for exchange rate policy. Unlike our other indices, it displays no persistent swings. Instead, it shows short-lived spikes near Ministry of Finance interventions in foreign exchange (FX) markets and during periods of high concern about large swings in the value of the yen. Notable episodes include the Asian financial crisis – when the yen depreciated sharply against the U.S. dollar, prompting both countries to intervene – strong yen appreciation in 2010 that triggered intervention, yen appreciation in 2011 amidst uncertainty around the US debt-ceiling debate, and the US debt downgrade. The index captures heightened uncertainty about exchange rate policy even when no FX intervention materialized. A good example is uncertainty related to sharp yen appreciation in 2016 and speculation about the possibilities for FX intervention.

Figure 7.
Figure 7.

Exchange Rate Policy Uncertainty Index (1987M1–2017M3)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Authors’ calculations.A: October 1987. Black Monday. Sharp yen appreciation against US dollar and FX intervention. B: December 1987. FX intervention with the US and Europe to stem yen appreciation. C: September 1992. European currency crisis with temporary suspension of ERM, and continued yen appreciation against the US dollar amid uncertainty around US presidential election. D: April 1993. Rapid yen appreciation, intervention by Japan and the US. E: August 1993. Continued yen appreciation, FX intervention, uncertainty about coordinated intervention with the US. F: June 1994. Excessive yen appreciation, Japan intervenes in the FX market, joint intervention together with the US and Europe. G: March 1995. Japan, US and Europe again intervene in effort to stem yen appreciation. H: August 1995. Japan, US and Europe conduct joint dollar-buying intervention to support U.S. dollar. I: June 1998. Concerns about rapid yen depreciation and mounting concerns over the financial system, severe downturn in Japan and Asian financial crisis. Japan and US intervene to support yen. J: September 1999. Rapid yen appreciation against US dollar prompts intervention. K: September 2000. Large Euro depreciation triggers debate and uncertainty about coordinated intervention, L: September 2001. 9/11 attacks M: June 2002. Yen appreciation and intervention. N: January 2003-March 2004. Large, sustained FX intervention through 2003. O: August-September 2010. Debate over yen appreciation and coordinated intervention. P: March 2011. Great East Japan earthquake triggers sharp yen appreciation and coordinated intervention with US and Europe. Q: August 2011. Sharp yen appreciation, FX intervention, and US debt-ceiling crisis. R: June 2012. European sovereign debt crisis and yen appreciation. S: May-June 2016. Rapid yen appreciation. Uncertainty over Brexit and FX intervention.Note: Shaded areas indicate periods of FX intervention.

Relationship to Other Economic Uncertainty Measures

As seen in Table 3, our overall Japan EPU index correlates at above 0.5 with option-implied volatilities for the Japanese stock market and for the yen-dollar exchange rate. Figure 8 reveals notable similarities between the EPU index and implied equity volatility, especially during the global financial crisis. Each measure exhibits distinct dynamics as well. For example, the implied equity market volatility falls rapidly after the global financial crisis, but the EPU index does not. The EPU index reacts much more strongly to the Asian financial crisis, and it is highly elevated during much of 2015 and 2016, unlike stock market volatility.

Table 3.

Correlation of Japan EPU Indices with Other Uncertainty Measures

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Note: Equity market volatility is the Nikkei Stock Average Volatility Index over one month calculated from Nikkei 225 futures and options. Exchange rate volatility is the option implied volatility over the next month for the USD-Japanese yen exchange rate. Interest rate volatility is the option-implied volatility over the next three months based on Japanese government bonds with 1- year tenor. The political uncertainty measure from Ito (2016) reflects the relative approval ratings of ruling and opposition parties. The Global EPU index from Davis (2016) is the GDP-weighted average of newspaper-based EPU indices for 18 countries. The EPU indices for the US, Japan and Europe are from Baker et al. (2016).
Figure 8.
Figure 8.

Japan EPU Index and Option-Implied Volatility of Nikkei Equity Index (1987M1–2017M3)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: NIKKEI and authors’ calculations.

Our Japan EPU indices also correlate positively with policy and economic uncertainty measures for other advanced economies and regions. This pattern points to common forces behind uncertainty movements in Japan and other major economies. The cross-country correlations are higher since the global financial crisis. For example, the correlation of our Japan EPU index and EPU indices for the US and Europe are about 0.3 in the pre-2007 period and 0.6 for the 2007–2016 period.

Figure 9 compares our fiscal policy uncertainty index with Ito’s measure of political uncertainty for Japan. The two measures reflect some of the same underlying developments. For example, both rose during 1997–98, peaking with the LDP’s defeat in July 1998 and the resulting Twisted Diet. They rose again in the 2007–12 period characterized by frequent turnover of the Prime Minister. The two indices correlate at 0.31 in monthly data and about 0.44 at the annual frequency. In contrast, Ito’s political uncertainty index correlates at only 0.07 with our uncertainty index for monetary policy. These results reassure us that our monetary and fiscal policy indices capture some distinct sources of uncertainty.

Figure 9.
Figure 9.

Our Fiscal Policy Uncertainty Index Compared to Ito’s Political Uncertainty Index (1987M1–2017M3)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Sources: Ito (2016) and authors’ calculations.Note: The blue lines indicate changes in Prime Minister.

Proximate Sources of Economic Policy Uncertainty in Japan

Figure 10 provides information about the proximate sources of policy uncertainty, and how those sources vary through time. On average, 57 percent of EPU articles contain one or more of the fiscal policy terms in Table 2, 27 percent contain monetary policy terms, 8 percent contain trade policy terms, and only 3 percent refer to exchange rate policy terms.12 These results strongly point to fiscal matters as the leading source of policy uncertainty in Japan. The fiscal policy share of EPU articles fell to relatively low levels in the early1990s and again in the 2006-07 period, before rising to high levels during and after the global financial crisis. The monetary policy share fluctuates around an upward drift and reaches its highest levels of about 30 percent near the end of our sample period. The share of EPU articles that discuss currency and trade policy matters are modest throughout the sample, although the trade policy uncertainty share has risen persistently since 2011.

Figure 10.
Figure 10.

Proximate Sources of Economic Policy Uncertainty

(Percent of Overall EPU Index, 12-month MA)

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

The Interplay between Policy Uncertainty and Economic Performance

As suggested by the foregoing discussion and our annotated charts, the interplay between policy uncertainty and economic performance is complex. Causal effects can operate in both directions, and rather differently across episodes. The potential for negative shocks to create policy uncertainty depends on the underlying environment, which in turn is shaped by previous policy decisions and institutions. For example, the case for discretionary fiscal stimulus in response to negative shocks is weaker when robust automatic fiscal stabilizers are in place. That is, the presence of automatic fiscal stabilizers diminishes the need for discretionary fiscal stimulus, and the political conflicts and policy uncertainty that often accompanies efforts to deploy discretionary fiscal tools. As a separate point, policy uncertainty may co-move with other hard-to-measure factors that influence, or are influenced by, economic performance. These factors include confidence about future economic performance, political polarization, and governance quality in the public sector.

This complexity is evident in the behavior of our policy uncertainty indices for Japan. Contested elections, major political transitions and Twisted Diet outcomes are often associated with higher levels of overall policy uncertainty and fiscal policy uncertainty (Figures 1 and 2). Prime Minister Abe’s election at the end of 2012 brought greater political stability, a clearer policy direction, and several years of declining or low policy uncertainty (Figure 1). A similar pattern held during the long tenure of Prime Minister Koizumi (Figure 1). It seems likely that these periods of political stability contributed to a moderation of policy uncertainty, and that a relatively benign or hopeful economic outlook during these episodes helped sustain stable political leadership.

Leadership transitions and policy shifts at the Bank of Japan sometimes brought spikes in monetary policy uncertainty (Figure 3). While leadership changes are inevitable and major developments may require policy shifts, their impact on economic uncertainty depends on previously established institutions and policy frameworks. Clear communications about the objectives of monetary policy, backed by strong analytical and empirical underpinnings, are likely to bring more continuity in the conduct of monetary policy, less anxiety and uncertainty about its future direction, and greater confidence about economic performance.

To appreciate how the past conduct of monetary policy shapes the current policy environment – and the scope for negative shocks to trigger a rise in policy uncertainty – consider recent proposals to raise the target rate of inflation (e.g., Blanchard et al., 2010 and Ball, 2014). The logic behind these proposals is straightforward: Raising the underlying rate of inflation reduces the likelihood that monetary policy becomes constrained by the zero lower bound on nominal interest rates during future downturns. In this way, a higher target rate enlarges the scope for using traditional monetary policy tools to stabilize economic activity and lessens the need for quantitative easing, forward guidance, direct credit market interventions and discretionary fiscal stimulus. Because less is known about the effectiveness of less conventional policy tools, their use involves greater uncertainty about effects. Heavy reliance on unconventional tools may also erode political support for the central bank, undermining sound monetary policy in the future.

Several episodes in recent decades illustrate the potential for negative economic shocks to create high levels of economic uncertainty. Examples include the Asian Financial Crisis, the downturn of 2001–02 and the Global Financial Crisis of 2008–09, all of which led to spikes in our measures of fiscal and monetary policy uncertainty (Figures 2 and 3). The experience of Asian countries during the Asian Financial Crisis also illustrates how past policy decisions shape the contemporaneous response of policy uncertainty to negative shocks. The build-up of financial excesses, funded through large dollar-denominated debts in the banking system and the private sector, made some Asian economies highly vulnerable to exchange rate adjustments. This vulnerability accentuated policy uncertainty during the Asian Financial Crisis. In contrast, stronger policy frameworks, better financial supervision and larger reserve buffers helped Asian economies weather the Global Financial Crisis under much better terms. See Davis (2017) for a broader discussion of how sound regulatory design can temper policy uncertainty.

IV. Policy Uncertainty and Aggregate Economic Performance

We consider VAR models that yield output, employment, consumption and investment responses to Cholesky-identified EPU innovations. Specifically, we estimate VAR models using data on the (natural) log of our Japan EPU indices, log Nikkei stock price index, nominal interest rate (yields on 2-year JGBs), log employment, log of GDP or industrial production (or major components), log household consumption expenditures or synthetic consumption index, and log gross private investment. Our sample for the baseline VAR model runs from 1994M1 to 2016M12 for monthly data and from 1987Q1 to 2016Q4 for quarterly data13. We use two lags in all VAR specifications.14 Our specifications rely on standard Cholesky decompositions to identify shocks, with log Japan EPU ordered first unless noted otherwise.15

Figure A.3 resents the time series of EPU shocks (in standardized units) identified from the monthly and quarterly VAR systems. At the monthly frequency, the largest EPU shock takes place in 2008M10 during the global financial crisis, followed by 2011M8 (U.S. debt downgrade, concerns over European debt crisis, and PM Kan’s resignation and the DPJ’s leadership election) and 1997M11 (policy debates about fiscal consolidation and Asian financial crisis). The European debt crisis in 2010 also led to a very large and positive EPU shock. It’s worth noting that large, positive EPU shocks sometimes occur during expansions, as in 2010M5, and 2011M8.

According to our baseline monthly results in Figure 11, upward EPU innovations foreshadow statistically significant declines in output, employment and consumption expenditures. Gray shading shows 95 percent confidence intervals. A unit standard deviation EPU innovation yields a peak estimated fall after about one year of 0.8 percent in industrial production and 0.2 percent in tertiary sector activity. We also find a smaller, marginally significant and less persistent response in consumption. The employment response is modest in size but highly persistent. While we do not measure gross investment at a monthly frequency, a breakdown of monthly IP data reveals much larger estimated output responses in sectors that produce investment goods.16 Figure A.4 shows that results for our fiscal policy uncertainty index are very similar to results for the overall EPU index, while results for monetary policy uncertainty are somewhat weaker.

Figure 11.
Figure 11.

Impulse Responses to Unit Standard Deviation EPU Innovation, Monthly Data

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

The quarterly VAR results in Figure 12 also show that upward EPU innovations foreshadow weaker aggregate performance. Specifically, a unit standard deviation upward EPU innovation foreshadows a peak fall in real GDP of about 0.3 percent after one year. The employment response is smaller but more drawn out. The investment response peaks at an estimated 1 percent. Figure 13 shows the historical contribution of EPU shocks to fluctuations in real GDP and investment. EPU shocks account for sizable movements in both variables—with peak investment and GDP swings of about 6 and 2 percent, respectively. EPU-induced movements are most pronounced in 1997–1999, 2001–2002 and 2008–2012.

Figure 12.
Figure 12.

Impulse Responses to Unit Standard Deviation EPU Innovation, Quarterly Data

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Figure 13.
Figure 13.

Historical Contribution of Japan EPU Shocks to GDP and Investment Fluctuations, Quarterly Data

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Figure 14 displays estimated real GDP responses to EPU innovations for alternative specifications and samples in the quarterly data. The basic pattern whereby upward EPU innovations foreshadow future output declines is robust to alternative Cholesky orderings, the inclusion of option-implied equity price volatility in the VAR system, and the inclusion of the Global EPU index from Davis (2016). These modifications to the VAR specification and identification assumptions lead to somewhat smaller output responses and somewhat wider confidence intervals. Discarding data after 2006 also yields somewhat smaller responses. If we instead restrict attention to the post-1995 period when the BOJ was up against the zero lower bound, we obtain larger responses, consistent with our priors.

Figure 14.
Figure 14.

Robustness to Alternative VAR Specifications with Quarterly Data: GDP Impulse Responses to a Unit Standard Deviation Japan EPU Innovation

Citation: IMF Working Papers 2017, 128; 10.5089/9781484300671.001.A001

Broadly speaking, we see three ways to interpret our VAR-based evidence. Under the first interpretation, an upward EPU innovation corresponds to an unforeseen policy uncertainty shock that causes the worsening of macroeconomic performance through real options effects, cost-of-capital effects or other mechanisms. Under the second interpretation, an upward EPU innovation captures bad news about the economic outlook that is not (fully) captured by the other variables in the VAR system, and that bad news triggers a rise in EPU that has harmful effects on the economy. Under this interpretation, EPU amplifies and propagates a causal impulse that originates elsewhere. Third, EPU has no role as either an impulse or a propagation mechanism; instead, it simply acts as a useful summary statistic for information missing from the other variables in our system. This third interpretation is hard to fully reconcile with the evidence of policy uncertainty effects in studies that use micro data, which allows for more compelling identification strategies. See, for example, Handley and Limao (2015), Baker et al. (2016), Gulen and Ion (2016), and Hassan et al. (2016).

Finally, Figure A.5 compares (a) the impulse responses of gross investment and GDP to policy uncertainty shocks using our Japan EPU index to (b) the corresponding responses using the Japan EPU index in Baker et al. (2016). For both investment and GDP, our Japan EPU index generates larger impulse responses and somewhat tighter confidence bands.17 These comparisons highlight the benefits from the additional steps we undertook to refine and improve the original Japan EPU index in Baker et al. (2016).

V. Concluding Remarks

We construct several new measures of economic policy uncertainty for Japan. Our measures reflect frequency counts of articles in major Japanese newspapers that contain specific terms related to the economy, policy matters and uncertainty.

Our overall EPU index co-varies positively with implied volatilities for Japanese equities, exchange rates and interest rates, and with a survey-based measure of political uncertainty. Our Japan EPU index rises around contested national elections and major leadership transitions. It peaks during the Asian Financial Crisis and in reaction to the Lehman Brothers failure, U.S. debt-ceiling fight in 2011, Brexit referendum, and Japan’s recent consumption tax-hike deferral. Terms related to fiscal policy appear in about 57 percent of all articles that meet our EPU criteria. Terms related to monetary policy appear in about 27 percent, while terms related to trade and exchange rate policy appear less often. These results point to fiscal policy concerns as the most important proximate source of policy uncertainty in Japan.

In VAR investigations, upward EPU innovations foreshadow declines in aggregate employment, output, consumption and investment. Investment responds much more than consumption expenditures, and output responds much more in sectors that produce capital goods. These results survive when we include option-implied equity price volatility in the VAR system. When we include a Global EPU measure, both Japan EPU and Global EPU shocks yield material, statistically significant output and investment responses. This result suggests the effects of policy uncertainty shocks spill across national borders, in line with other evidence in Colombo (2013), International Monetary Fund (2013), Klössner and Sekkel (2014), Julio and Yook (2016), and Costantinescu (2017).

While it is hard to establish causal effects, we see our results as favoring the view that high policy uncertainty undermines macroeconomic performance. It may do so by acting as an impulse behind fluctuations, as a mechanism for amplifying and propagating causal impulses that originate elsewhere, or both. We also stress that past policy decisions and institutions shape the policy uncertainty response to contemporaneous economic shocks. In particular, well-designed policy institution and rules can limit the scope for negative shocks to trigger large jumps in policy uncertainty.

Our evidence and discussion suggest that credible policy plans and strong policy frameworks can favorably influence macroeconomic performance by, in part, reducing policy uncertainty. In the Japanese context, credible plans to follow through on trade reforms would promote trade-creating investments. Credible medium-term budget plans would foster confidence about Japan’s fiscal trajectory. Further efforts to improve the BOJ’s communications framework would lessen uncertainty about the direction of monetary policy.

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