Does the effectiveness of monetary policy depend on the choice of policy instrument? Empirical evidence from South Korea

Zuniga, Martha Cruz; Senbet, Dawit Article Does the effectiveness of monetary policy depend on the choice of policy instrument? Empirical evidence from South Korea Journal of Central Banking Theory and Practice Provided in Cooperation with: Central Bank of Montenegro, Podgorica Suggested Citation: Zuniga, Martha Cruz; Senbet, Dawit (2023) : Does the effectiveness of monetary policy depend on the choice of policy instrument? Empirical evidence from South Korea, Journal of Central Banking Theory and Practice, ISSN 2336-9205, Sciendo, Warsaw, Vol. 12, Iss. 2, pp. 239-265, https://doi.org/10.2478/jcbtp-2023-0021 This Version is available at: https://hdl.handle.net/10419/299079 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 239 * Department of Economics, The Catholic University of America, Washington, D.C., USA E-mail: cruzzunig[email protected]u ** Department of Economics, University of Northern Colorado, Greeley, CO, USA E-mail: [email protected] Journal of Central Banking Theory and Practice, 2023, 2, pp. 239-265 Received: 05 June 2022; accepted: 21 November 2022 UDK: 338.23:336.74(519.5) DOI: 10.2478/jcbtp-2023-0021 Martha Cruz Zuniga *, Dawit Senbet ** Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea Abstract: This study provides robust evidence on how the choice of the policy instrument for monetary policy influences its impact on economic activity. We study the case of South Korea for the period 1980-2017. We use FAVAR models that allow a comprehensive exploration of different areas of economic activity by overcoming limitations on a number of variables that can be included in the analysis in a traditional VAR model. Following the actual use of instruments, we test the effectiveness of monetary policy in two separate periods: 1980-1999, when the Bank of Korea mostly used M2 as the policy instrument; and then 2000-2017, when interest rate was the policy instrument. Our results show that monetary policy that uses interest rate as the policy instrument is markedly more effective in economic activity than M2. This is observable in the reaction from prices as well as variables that measure industrial production. In contrast, the impact of M2 mostly occurs in prices and it is short lived. We use robustness checks that switch the use of instrument for each subperiod and also test the use of each policy instrument for the entire period of analysis. The results hold, interest rates as policy instrument of monetary policy are more effective than M2. Keywords: monetary policy, policy instrument, VAR, FAVAR, impulse response function. JEL classification: C55, E52, E58. Journal of Central Banking Theory and Practice 240 1. Introduction Understanding the impact of monetary policy actions in a domestic economy is essential for all economic agents, not just policy makers. Clarida, Galí and Gertler (1999) and Güler (2021) stressed the importance of gaining a better understanding on how monetary policy operates and that in considering open economies, the role of exchange rate regime and consumer prices becomes particularly relevant. Over time, countries have adopted different targets for monetary policy. Bernanke and Mishkin (1997) explain how during the 1970s countries used policies with money-growth targets, while starting in the 1980s, central banks began to switch to policies that reduced inflation, which led to some countries adopting the now well-known inflation-targeting regimes. However, not all regimes were successful; Canada, for instance, switched to inflation targeting after unsuccessful pursuing a money growth-targeting regime (Bernanke and Mishkin, 1997). South Korea makes an interesting case of study for monetary policy actions. The fourth largest economy of Asia (after China, India and Japan), with a success story as one of the Asian tigers but also greatly impacted during the 1997 Asian crisis, later engaged in implementing macroeconomic reforms that would provide more stability to the economy. The Bank of Korea, its central bank, explicitly regards price stability as the central objective of monetary policy in its mandate (Bank of Korea, 2002) with the ultimate goal of sustainable economic growth. The Bank of Korea Act of April 1998 stipulates that the bank should set an annual inflation target that must be achieved. For instance, the inflation target for 2002 was 3.1% (Bank of Korea, 2002) while it had a target around 2% in 2017 (Bank of Korea, 2017). Inflation in South Korea has fluctuated over time. Rapid economic growth and an average inflation of 14% occurred in the 1970s. The implementation of stabilization policies in the 1980s and 1990s reduced inflation to single digits, except in 1998, after the Asian financial crises (Bank of Korea, 2002). While M1 growth was the main indicator during the 1970s, the lack of success on reaching its target led the central bank to switch, starting in 1979, to the use of M2 as the leading monetary indicator. During the 1980s and most of the 1990s, this monetary targeting regime continued even when other economies were abandoning it as a disconnection between monetary aggregates and inflation became apparent. The annual target for money growth declined from 20-25% in 1980 to 11.5-15% in 1996 (Bank of Korea, 2002). Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 241 An inflation targeting regime started in South Korea after 1998. Obstfeld (2014) indicates that it was with the IMF encouragement that South Korea introduced inflation targeting and that in addition to this new regime, institutional reforms were adopted and gave the central bank more independence and transparency. Targets for CPI inflation rates started to be announced after the adoption of inflation targeting. Because South Korea adopted the inflation-targeting regime in the aftermath of the 1997 Asian currency crisis, the first year of the regime inflation was higher than in the pre-regime (Aleem and Lahiani, 2014). After the initial adoption, however, comparisons with actual values showed a strong performance close to the targets, which points out the success of monetary policy actions (Obstfeld, 2014). Importantly, with the revised act, the central bank abandoned a dual mandate of stability of money and soundness of the banking system and focused on price stability as the main goal for monetary policy (Hoffmaister, 2001 and Krušković, 2022). During the 1997 financial crisis, monetary policy was not very effective. Rousseau and Kim (2017) investigated the role of monetary shocks in the transmission of the crisis to the economy. The findings led to the conclusion that the ratio of commercial bills dishonored with respect to the total value of bills better explains the decline in industrial production than the central bank’ decreases in the real stock of money. They attribute the more accurate role of dishonored bills ratio to the proxy, and this variable represents, for the cost of credit and the consequent effect on small and medium enterprises, a very important component of the economy of the country. It also suggests the presence of a credit channel, where the real sector was more affected by the rise in the costs of financial intermediation than by the decline in the supply of money. In the same line, Oh (1999), discusses how the results of impulse response functions analysis indicate that the increases in the policy rate reduce consumer prices and that such effect persist in the long run. The effects of the shock to the policy rate on consumer prices, real exchange rate and industrial production are stronger than those coming from changes in money. Thus, due to financial innovation and liberalization, there has been a decrease in the effectiveness of the monetary channel, while the interest channel has increased in relevance. This, the author mentions, is key to the 1998 decision of the Central Bank to switch to inflation targeting regime. After the crisis and with the adoption of inflation targeting, the effectiveness of monetary policy appears to have improved. Lim (2003) indicates that since its adoption in 1998, the inflation targeting regime that works in the country by adjusting interest rates has been successful in the control of the variability of Journal of Central Banking Theory and Practice 242 inflation and output. On the other hand, Kim and Park (2005) show that after the adoption of the new regime the country has experienced a declining trend in the deviation of inflation from its target as well as a slowdown in output growth. Though inflation targeting has helped the reduction of inflation volatility, “the decrease in the size of the standard deviation of inflation due to the propagation of inflation shocks is larger than that of inflation shocks itself. This finding suggests that the reduction in inflation volatility is not mainly due to the decrease in shocks to inflation” (p. 147). Kim, Kim and Suh (2009) explain that after the Asian crisis of 1997, South Korea switched exchange rate regimes, going from a managed system towards a freefloating regime with the elimination of bands and expanding capital liberalization. Reforms following the crisis include the introduction of prudential regulation and supervision, improvement of corporate governance, and the adoption of inflation targeting regime, that is seen as a landmark of a proper-functioning financial system. According to Han, Lee and Yun (2014), after the financial crisis, the response of bank lending rates to policy rate changes has expanded, which has been magnified by the changes in the lending market conditions. The only exception is household lending rates, where the transmission appears reduced. Overall, more response in bank lending rates is found under expansionary policy (lowering policy rates) than under contractionary policy (cuts in policy rates). Analyzing the impact of monetary policy on the stock market, Sohn and Eom (2007) show that the response is immediate and stronger just after a policy shock, which is attributed to the efficiency of the stock market in incorporating and adjusting expectations and transaction behavior. Thus, stock market volatility can decrease with regular announcements such as those on the inflation targeting regime. Contrary to these findings, Sohn, Sung and Kwon (2006) find that monetary policy signals or announcements increase the volatility in financial variables with little impact on their levels, which the authors assess as an inability of monetary authorities to minimize the instability of the financial system. The latter is explained as a result of the difficulty in using past announcements and information from financial variables in forecasting future performance. On comparing the effects of a given variable on two periods of time, Kim (2007) investigates the changes in the cost of capital as a channel for monetary transmission by comparing the high inflation period of the country (1988-1998) with the low inflation period that followed the adoption of inflation targeting (1999-2004). Using a cost elasticities approach, the author finds that the long run user cost Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 243 elasticity fell dramatically in the low inflation period, which reflects for firms that investment has become less sensitive to the changes in cost. Moreover, an increase in interest rates results in more modest decline in the low inflation period than in the previous high inflation period, implying a more weakened interest rate channel in the low inflation period mostly due to the fall in user cost elasticity. Relating to costs, Yie (2008) investigates the existence of a cost channel in the transmission process in South Korea. The author finds the relevance of this channel after contractionary monetary policy before the 1997 crisis, but a dramatic decline after 1997. This change is accredited to the longer adjustment on output prices and the decline in the cost of capital adjustment after the crisis. When the banking sector is efficient in loan provision, monetary policy impacts the economy through changes in the aggregate demand (Demirbas and Can, 2022). The recent history of monetary policy in South Korea, relevant to this paper, starts in the late 1970s. As explained by the Bank of Korea (2002), from initially using M1 as the policy instrument, instability of this tool moved the bank to replace it with the use M2 in 1979, which also signaled a full focus on monetary targeting by the bank. This targeting persisted until the 1990s, even as more developed countries started to switch to interest rate-based policy instruments, because interest rates were regulated in Korea during those years. There were several episodes when targets were not reached due to oil shocks as well as current account surpluses. The money targets were based on the economic conditions that included the rate of economic growth, price fluctuation and money velocity. A significant increase in money in trust accounts in commercial banks were used for short-term financial transactions and were not subjected to reserve requirements generated instability in M2 as monetary indicator. Changes in regulation of the trust accounts by the Bank of Korea in efforts to control the instability resulted in money flowing from the trust accounts to commercial banks’ time and savings deposits, which in turn, increase the rate of growth of M2 from mid-1995 to mid-1996. This prompted the bank to adopt, in mid-1996, an additional policy instrument, MCT made of M2, certificates of deposit (CDs) and money-in-trust while also keeping M2. MCT was considered the main policy instrument; however, a 2% reserve requirement on CDs, imposed in 1997, significantly affected the growth of MCT as well as its usefulness as a policy instrument, prompting the Bank of Korea to consider the validity of maintaining money as its main instrument in the conduction of monetary policy. The bank decided to adopt inflation targeting in April 1998; it used M3 as a transitory policy instrument and received initial advice in the process from the IMF. September 1998 marked the first time the bank used interest rates as an operating target with an official announcement of using them as target in May 1999. Interest rates remain the policy instrument Journal of Central Banking Theory and Practice 244 for monetary policy in South Korea. For the purposes of our study, we divide the period of policy instruments in two, the first from 1980 to 1999 where money was the main target, and we choose M2 as the instrument as per the discussion above since it was the main instrument during the period. The second period of analysis is 2000-2017 with interest rates as the policy instrument. Overall, studies about the effects of monetary policy in South Korea tend to focus on a specific channel (e.g., cost channel, exchange rate channel) or a specific variable (e.g., inflation) and with the use of structural VARs. The contribution of our paper in this area is a more comprehensive study about the effectiveness of monetary policy in economic activity by 1) investigating comparatively two different regimes: money target versus interest rate target; 2) analyzing the impact of policy actions in a wider set of macroeconomic variables by using the methodology that permits this analysis, FAVAR; and 3) by analyzing a longer period, 1980-2017. To the best of our knowledge, this is the first paper that combinedly works on these aspects for South Korea. 2. The Model The Vector Autoregressive (VAR) model was developed by Sims (1980). It did not take much time for those simple and elegant VAR models to replace the cumbersome macro-econometric models, which were used as a standard in analyzing monetary policy or forecasting macroeconomic activities. The VAR models suffer from limited information set since they cannot typically handle more than four to eight variables, while monetary authorities throughout the world analyze literally hundreds of variables in making policy decisions. Consequently, as time continued, the limitations of the VAR models became apparent. During the same time frame, dynamic factor models were also introduced and gained popularity (Sargent and Sims, 1977; Geweke, 1977). Those models were used to condense or summarize information from large data sets into few variables, known as factors. Bernanke, Boivin and Eliasz (2005) have successfully combined factor modes with VAR to develop what is called the Factor-Augmented Vector Autoregressive (FAVAR) models. In doing so, they managed to incorporate any number of macroeconomic variables into the VAR models, thereby solving its major drawback of limited information set. According to Bernanke et al. (2005), there are at least three potential problems associated with VAR models that could be solved by FAVAR models. First, policy makers have mode information sets (by analyzing hundreds of variables) as op- Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 245 posed to the few variables included by the standard VAR models. It follows that the impulse response functions we generate from VAR models could be contaminated. This could be solved by incorporating potentially all relevant macroeconomic variables analyzed by policy makers into our models, i.e., FAVAR models. Second, the Standard VAR requires us to represent economic activity by a single variable such as the gross domestic product, industrial production, or unemployment rate. However, with FAVAR models, it is possible to represent economic activity as an unobserved variable determined by many observed variables. For example, we can construct an “economic activity” factor from numerous macroeconomic variables that constitute economic activity. Finally, with FAVAR models, we can generate impulse response functions for all of the variables included in the model (no matter how many), as opposed to the four to eight variables of the VAR models. The underlying assumption with the FAVAR models is that the economy is driven by few factors that could be generated from numerous macroeconomic variables and idiosyncratic errors (Favero, Marcellino and Neglia, 2005). Following Bernanke et al. (2005), Stock and Watson (2005), Senbet (2008) and Zuniga (2011), we developed the FAVAR model as follows. Assume that Yt is a dynamic factor model expressed as a distributed lag of a small number of unobserved factors and idiosyncratic disturbances that are assumed to be serially correlated. (1) (2) Where Ft is a vector of unobserved dynamic factors, is an dynamic factor loadings and is white noise. Also assume that factors and disturbances are not correlated. From equation (2), and hence (1) becomes (3) Where Define the evolution of factors as (4) Journal of Central Banking Theory and Practice 246 Where ηt is a disturbance vector. Substituting (4) into (3) and rearranging (5) Where Combining equation (5) with the factor evolution equation (4) yields the FAVAR model: (6) The VAR model is a special case of the FAVAR model expressed above. If we assume the terms in are all zero, the system boils down to which is exactly the VAR model. However, since the factors are not observed, it is not possible to directly estimate the FAVAR model given in equation 6. Bernanke et al. (2005) solve that problem by assuming that the factors can be inferred from the many observable macroeconomic variables (“informational” variables) analyzed by policy makers. Assume that the “informational” time series variables, observed by policy makers, are given by vector . The number of informational variables should be greater than the number of factors and the number of policy variables in other words, . The assumption by Bernanke et al. (2005) that factors can be inferred from leads to the following equation: (7) Where is and is . It is also easy to see that is vector of factors, is vector of policy instruments and is vector of error terms with zero mean and no serial correlation. For our study, since we use one policy instrument at a time, this means . Our next task is to estimate the unknown factors using the principal component analysis (Bernanke et al., 2005). First, we estimate the factors using all variables in denoted by . However, the space covered by could overlap with that of , and this must be corrected to create independence between the two. We do that by dividing the dataset into fast-moving variables and slowmoving variables. The fast-moving variables are assumed to be highly sensitive (contemporaneously responsive) to policy shocks, such as bond prices, exchange Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 253 pothetical monetary policy instrument) has far less impact on economic activity than the interest rate shock (actual monetary policy instrument). The second robustness check was to combine the entire period (1980-2017) and analyze the impacts of the shocks to money (M2) growth, as well as the shocks to the interest rate. In effect, we are presenting the scenario where the Bank of Korea starts using M2 (or interest rate) as policy instrument and sticks to it throughout the entire period. Again, the results clearly show that interest rate as policy instrument was by far more effective than M2. It is important to note that had the Bank of Korea actually used M2 (or the interest rate) as policy instrument during this entire period (1980-2017), the impulse response functions might have looked different. However, our objective here is to show the relative effectiveness of the two policy instruments under similar assumptions. In that, we have achieved our objective of showing that the interest rate is far more effective compared to money growth as policy instrument in South Korea. We agree that the Bank of Korea made a correct policy call by switching its instrument from M2 growth rate to the base rate by late 1990s. In doing so, monetary policy became more effective in influencing the macroeconomic variables of the country. Journal of Central Banking Theory and Practice 254 5. Conclusions In this study, we assess the effect that choosing a policy instrument has on the impact of monetary policy on economic activity. We focus on two instruments in South Korea for the period 1980-2017, money as measured by M2 and interest rate. The Bank of Korea had used M2 as its instrument until 1999, and then switched to interest rate. Considering this timeframe in mind and with the use of the FAVAR model, we explore the impact of monetary policy shocks on economic activity and compare the effectiveness by looking at the reaction from impulse responses of variables of interest. Considering economy-specific estimates, we document the stronger impact on economic activity from using interest rate as the policy instrument for monetary policy, in contrast to a quite minimal response of using money as the instrument. In the latter case, there are short-lived responses mostly on variables representing prices. In the former, responses in real economic activity can be identified. We further test the robustness of these findings by switching the instruments and exploring the effect of interest rates in the first period, 1980-1999, while using money as the policy instrument for the second period of analysis, 2000-2017. The results are consistent with the previous findings: shocks to interest rates have a larger impact on economic activity than the responses found in shocks to M2. Extending the robustness checks, we test the use of each policy instrument, M2 or interest rate, for the entire period of analysis of 1980-2017. Consistently, we find monetary policy is more effective when interest rate is the policy instrument. Particularly, the effects on real economic activity appear mainly when interest rates are used, not in the adoption of M2. This means that the reaction to monetary policy shocks is not irrespective of the policy instrument. In short, our results suggest that interest rates as the monetary policy instrument do have a significant impact on economic activity in emerging markets such as South Korea. Our empirical results also provide no support for the argument that money is likely to be a successful instrument for monetary policy. This is relevant for many emerging and developing economies that still use money -in different measuresas their policy instrument. Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 255 Figure 1. Impulse responses to a shock in M2 for the period of 1980-1998, generated from FAVAR model (Y = M2, Five Factors). Note: The dotted lines represent a 95% confidence band around the impulse response functions. Source: Authors` calculations Journal of Central Banking Theory and Practice 256 Figure 2. Impulse responses to a shock in the base rate for the period of 1999-2017, generated from FAVAR model (Y = base rate, Eleven Factors). Note: The dotted lines represent a 95% confidence band around the impulse response functions. Source: Authors` calculations Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 257 Figure 3. Impulse responses to a shock in the base rate for the period of 1980-1998, generated from FAVAR model (Y = base rate, Seven Factors). Note: The dotted lines represent a 95% confidence band around the impulse response functions. Source: Authors` calculations Journal of Central Banking Theory and Practice 258 Figure 4. Impulse responses to a shock in M2 for the period of 1999-2017, generated from FAVAR model (Y = M2, Seven Factors). Note: The dotted lines represent a 95% confidence band around the impulse response functions. Source: Authors` calculations Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 259 Figure 5. Impulse responses to a shock in M2 for the period of 1980-2017, generated from FAVAR model (Y = M2, Seven Factors). Note: The dotted lines represent a 95% confidence band around the impulse response functions. Source: Authors` calculations Journal of Central Banking Theory and Practice 260 Figure 6. Impulse responses to a shock in the base rate for the period of 1980-2017, generated from FAVAR model (Y = base rate, Seven Factors). Note: The dotted lines represent a 95% confidence band around the impulse response functions. Source: Authors` calculations Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea 261 References 1. Aleem, A., and Lahiani, A. 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