Limited Financial Market Participations and Shocks in Business Cycles in Korea

Jung, Yongseung Article Limited Financial Market Participations and Shocks in Business Cycles in Korea East Asian Economic Review (EAER) Provided in Cooperation with: Korea Institute for International Economic Policy (KIEP), Sejong-si Suggested Citation: Jung, Yongseung (2024) : Limited Financial Market Participations and Shocks in Business Cycles in Korea, East Asian Economic Review (EAER), ISSN 2508-1667, Korea Institute for International Economic Policy (KIEP), Sejong-si, Vol. 28, Iss. 2, pp. 245-273, https://doi.org/10.11644/KIEP.EAER.2024.28.2.436 This Version is available at: https://hdl.handle.net/10419/316632 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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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/ PISSN 2508-1640 EISSN 2508-1667 an open access journal East Asian Economic Review vol. 28, no. 2 (June 2024) 245-273 https://dx.doi.org/10.11644/KIEP.EAER.2024.28.2.436 ⓒ Korea Institute for International Economic Policy Limited Financial Market Participations and Shocks in Business Cycles in Korea Yongseung Jung† Kyung Hee University [email protected] This paper sets up a small open new Keynesian economy model with constrained households and incomplete markets to address the driving forces of business cycles in Korea. It shows that there exists a substantial fraction of constrained households who cannot have access to financial market. Furthermore, the estimated model reveals that a TANK model is better than a RANK model in explaining business cycles in Korea. The effect of domestic productivity shock on Korean economy has dominated in the variations of output, while the contribution of the foreign productivity shock to the variations of output and inflation has increased after the Asian financial crisis. The monetary policy shock has dominated the variation of inflation at short and medium horizons. Keywords: Business Cycles, HtM, Korea, Maximum Likelihood Estimation, TANK JEL Classification: E32 I. Introduction A burgeoning of literature on the heterogeneous agent New Keynesian (HANK) model has contributed to understanding the transmission of monetary and fiscal policy over the business cycle. Market incompleteness and heterogeneity have been utilized to address the interaction between inequality and fiscal and monetary policy. Kaplan et al. (2018) show that the general equilibrium effect of an interest rate cut, operating through an increase of household income associated with the labor demand expansion, dominates the direct effect associated with the intertemporal substitution. Auclert et al. (2019) argue that the fiscal multipliers depend on the interaction of an intertemporal marginal propensity to consume, i.e., iMPC and deficit-financed fiscal policy and ID † Department of Economics, Kyung Hee University, Kyunheedae-ro 26, Dongdaemunku, Seoul, 02447, South Korea. I would like to thank for helpful comments from the participants in numerous institutes and anonymous referees. All errors are mine. 246 Yongseung Jung ⓒ Korea Institute for International Economic Policy only the HANK model can generate the empirical iMPC. McKay et al. (2016) address how the HANK model can solve the forward guidance puzzle arising from the representative agent new Keynesian (RANK hereafter) model. The quantitative HANK models that explicitly take into account heterogeneity and the feedback effects from equilibrium distributions to aggregates are successful in delivering the general equilibrium effect of exogenous shocks comparable to the one in the data. However, it is difficult to track the wealth distribution, as it is necessary to use nontrivial computational techniques to solve the equilibrium in the HANK models. The earlier literature on two-agent models to address the business cycle has emphasized the heterogeneity in shaping the transmission of monetary and fiscal policy. The two-agent new Keynesian (TANK) model with a minimal heterogeneity and analytical tractability has been utilized to understand and quantify the implications of heterogeneity in households. In the canonical TANK model, there is a constant fraction of constrained or hand-to-mouth (HtM hereafter) households who cannot have access to the financial market and have to consume their current income. Other fraction of households, called unconstrained or Ricardian households who can have access to financial market satisfy the Euler equation. Though the simple TANK model does not allow any idiosyncratic shock and endogenous fraction of constrained households, Debortoli and Galí (2019) show that the tractable TANK model can approximate the dynamics of the HANK model under comparable redistribution schemes.1 The open economy TANK model is isomorphic to the open economy representative agent new Keynesian (RANK) model. However, there are stark differences between a TANK model and a RANK model in open economy. First, the aggregate demand equation, i.e., the unconstrained household’s Euler equation in the TANK model is different from the one in the RANK model in that the former depends on the aggregate demand as well as the fraction of HtM households in the economy. Second, only consumption of unconstrained households matters to the risk-sharing in an open economy as HtM households cannot participate in financial markets. Finally, the NKPC and goods market clearing condition depends on consumption and income inequality between unconstrained households and HtM households. The question about the important role of financial frictions in shaping the business cycle in Korea has been actively debated in Korean academia and policy makers since 1 Bilbiie (2019) extends a simple TANK model to a tractable two agent heterogeneous agent model with idiosyncratic shock to address monetary and fiscal policy effect on consumption and output. Limited Financial Market Participations and Shocks in Business Cycles in Korea 247 ⓒ 2024 East Asian Economic Review the Korean government has adopted an export driven economic growth strategy from the 1960s. Some critics have been skeptical about the sustainability of the economic growth strategy in Korea where a substantial fraction of economically neglected households exists. They have criticized the structure of the Korean economy, since the economy which heavily depends on the rest of the world is too fragile to sustain its stable economic growth. In this paper, we address the following questions with a TANK model with incomplete markets. How important have the economically neglected households, i.e., the HtM households been in shaping the business cycle in Korea over time? Specifically, does the TANK model perform better than the RANK model in explaining business cycles in Korea? What kind of shock has been the main driving force in business cycles in Korea? What fraction of HtM households have been in Korea? Has the fraction of HtM households who cannot have access to financial markets increased in Korea over time during 1997 Asian financial crisis and the ongoing Great Moderation periods? For this purpose, we set up a small open economy TANK model with a simple heterogeneity along the lines of Bilbiie (2008) and Debortoli and Galí (2019). Specifically, we set up a small open economy TANK model with domestic and foreign productivity shocks, preference (or demand), and monetary shocks. We estimate the key parameters of the model with quarterly data spanning from 1970 to 2018 by employing maximum likelihood. In particular, we estimate the share of HtM households in Korea by dividing the sample periods into three subsample periods to look at how the share of HtM households has varied before and after 1997 Asian financial crisis and the ongoing Great Recession periods. Then, we examine, quantitatively and with the help of formal econometric methods, the importance of HtM households within the specified framework. Finally, we evaluate the relative importance of each shock and the relevance of financial frictions over the business cycle. Three important findings come from this paper. First, the fraction of HtM households in Korea increased over time in Korea. Furthermore, the estimated model reveals that the TANK model performs better than the RANK model in explaining business cycles in Korea. The likelihood ratio statistic shows that the model without HtM households is rejected by data. The estimated share of HtM households is about 0.2 in the first subsample period, 1976:3Q - 1996:3Q before the Asian financial crisis. However, it increased to about 0.4 during the second 248 Yongseung Jung ⓒ Korea Institute for International Economic Policy subsample periods. The low estimate of the HtM households before the Asian financial crisis seems to echo a high saving rate during a high economic growth era. Households who have been very optimistic about the future of the economy were willing to save their income for their children in terms of forced savings. When the high economic growth era has come to an end with the Asian financial crisis, a lifetime workplace has also disappeared, increasing the share of HtM households. The estimated share of HtM households roughly matches the estimated fraction of the HtM households in Jung and Kim (2019) who found using KLIPS (Korea Labor Institute Panel Survey) from 2001 to 2018. Second, the domestic productivity shock has dominated in explaining the variations of output at all horizons, while the foreign productivity shock and the preference have played an important role in the variation of inflation at the short and medium horizons after the Asian financial crisis as the Korean economy has liberalized the capital movements. The monetary policy shock has played a minor role in the variation of output in the whole sample period. The foreign productivity shock has been the most important factor in the variations of the international relative price in the whole sample period. Finally, the monetary policy shock has been the most important factor in the variation of inflation at short and medium horizons, while the foreign supply shock has heavily contributed to the fluctuation of inflation at medium and long horizons after the Great Recession. During the Great Recession periods, the monetary shock has dominated in explaining the variations of inflation as the monetary authority tries to stimulate the economy by manipulating its policy rate. The outline of the paper is follows. In section 2, we specify a simple TANK model. In section 3, we discuss an equilibrium and the implications of the model related to real activities and prices. In section 4, we present the quantitative implications of the model. Finally, concluding remarks are given in section 5. II. Model This section sets up a canonical TANK model with incomplete markets. In the home country, a share of 1-λ of households, i.e. unconstrained households have access to financial markets, while the remaining share λ of the households, i.e. constrained or HtM households do not trade any asset and simply consume their current labor income. Limited Financial Market Participations and Shocks in Business Cycles in Korea 249 ⓒ 2024 East Asian Economic Review 1. Households (1) Unconstrained households Unconstrained households can have access to international financial markets. They seek to maximize 𝒲,=𝐸∑𝛽exp (𝑣)𝑈𝐶,−,     ,0<𝛽<1, (1) where 𝑈𝐶,=,    for σ≠1, and 𝑈𝐶,=𝑙𝑛𝐶, for σ=1. 𝐸 denotes the expectation operator over all possible states of nature on history 𝑠 and 𝐶, and 𝑁, represent the unconstrained household’s consumption and labor hours in period t, respectively. Here 𝑣 is a preference shock which follows an AR(1) process as 𝑣=(1−𝜌)𝑣+𝜉,, 0<𝜌<1, where ξ, is an i.i.d., normally distributed process with mean 0 and variance 𝜎. 𝐶, is a composite consumption index defined by 𝐶,=󰇩𝜃𝐶,  +(1−𝜃)𝐶,  󰇪 , 𝜂>0 (2) Here 𝐶, and 𝐶, are indices of domestic unconstrained households’ home and foreign consumption goods. Note that η measures the substitutability between domestic and foreign goods, and θ∈[0,1] measures the degree of openness in goods market, i.e. the share of domestic consumption allocated to domestic goods. 𝐶, and 𝐶, take the following CES aggregator: 𝐶,=[ 𝐶(𝑖),    𝑑𝑖] ,𝐶,=[ 𝐶(𝑖),    𝑑𝑖] , ϵ>1 (3) where 𝜖 denotes the elasticity of substitution among goods within each category. Domestic unconstrained households are subject to a sequence of budget constraints. We assume incomplete asset markets where only one-period nominal riskless bonds 250 Yongseung Jung ⓒ Korea Institute for International Economic Policy denominated in home and foreign currency are traded in the international financial markets. Domestic unconstrained household’s budget constraint is given by 𝑃𝐶,+𝑅𝐵,+𝑅∗𝐵, ∗𝐹(𝜀𝐵, ∗𝑃)+Θ𝑉≤𝐵,+𝐵, ∗+ 𝑊𝑁,+Θ𝑉+𝑃𝐷,+𝑃𝑇𝑅,, (4) where 𝑃 and ℰ are the home consumer price index (CPI) and the nominal exchange rate in period t. Here Θ, 𝑉, and 𝐷, denote domestic share holdings, average market value of the corresponding shares, and the real dividends at time t, respectively. 𝐵, and 𝐵, ∗ are one-period domestic and foreign currency denominated riskless nominal bonds with the corresponding interest rates 𝑅 and 𝑅∗, respectively. Since the nonstationarity of the incomplete markets with riskless bonds complicates the task of approximating equilibrium dynamics, we assume that the international trade of foreign currency denominated bonds is subject to intermediation costs as in Benigno (2009) and Schmitt-Grohé and Uribe (2003). Specifically, the interest rate 𝑅∗𝐵, ∗𝐹(ℰ𝐵, ∗𝑃) faced by domestic unconstrained households is increasing in domestic country’s average foreign debt ℰ𝐵, ∗𝑃. That is, F′(.) > 0, and 𝐹𝑩, ∗=1 in the steady state where 𝑩, ∗≡ℰ𝐵, ∗𝑃. In similar, the budget constraint of the representative foreign households can be written as 𝑃∗𝐶∗+𝐵, ∗𝑅∗≤≤𝐵, ∗+𝑊∗𝑁∗+Γ, (5) where Γ is the intermediation profits from loans to the small country. First order conditions for the household implies that the equilibrium real exchange rate 𝑄 is determined by 𝐸[󰇡 ∗ ∗󰇢 ∗  ∗]=𝐹(𝐵, ∗)𝐸[𝑒𝑥𝑝(𝑣−𝑣), ,ℰ ℰ]. (6) The ratio of the consumer price index 𝑃 relative to the domestic price index 𝑃, is related to the terms of the terms of trade 𝑆=𝑃,𝑃,  as follows Limited Financial Market Participations and Shocks in Business Cycles in Korea 251 ⓒ 2024 East Asian Economic Review , ,=[(1−𝜃)+𝜃𝑆] ≡K(𝑆). (7) Finally, notice that intertemporal condition for domestic bond holdings β𝐸[𝑒𝑥𝑝(𝑣−𝑣), ,  ()]=1 (8) also holds, where 𝜋≡ −1 is the CPI inflation rate at time t. The risk-sharing condition in incomplete market can be log-linearized around the steady-state as follows 𝐸[𝑞]−𝑞=𝜎𝐸[𝑐,−𝑦 ∗]−σ(𝑐,−𝑦∗)+𝜁𝑏,+(1−𝜌)𝑣, (9) where 𝑏,≡𝑩,  and ζ is a risk premium or borrowing premium in the international market. The small letter 𝑥 denotes the log-linearization of the corresponding variable 𝑋 around its steady state X, 𝑥=𝑙𝑛(𝑋/𝑋). (2) Constrained households The HtM or constrained households who do not have any assets work for 𝑁, hours and consume their income determined in each period: 𝑃𝐶,=𝑊𝑁,, (10) where 𝐶, is HtM household's consumption in period t. HtM households seek to maximize their temporal utility function (𝑈,) subject to a budget constraint (10): 𝑈,≡𝑒𝑥𝑝(𝑣)[,   −,  ]. (11) HtM household’s optimization conditions are given by 𝑁, 𝐶, =𝑤 (12) 252 Yongseung Jung ⓒ Korea Institute for International Economic Policy and the budget constraint (10). Here 𝑤≡  is the real wage at time t. 2. Domestic Firms The domestic firms’ problem is standard. Each good is produced by a monopolistically competitive firm indexed by i∈[0,1] using a linear technology 𝑌(𝑖)=𝑒𝑥𝑝(𝑧)𝑁(𝑖). Here 𝑧 is an AR(1) process technology shock in home country at period t, i.e. 𝑧=(1−𝜌)𝑧+𝜉,, 0<𝜌<1, where ξ, is an i.i.d., normally distributed process with mean 0 and variance 𝜎. 𝑌(𝑖) and 𝑁(𝑖) represent the corresponding firm's output and total labor input, respectively. Since the labor market is perfectly competitive, the cost minimization implies that (1 −τ)𝑤=𝑚𝑐𝑒𝑥𝑝(𝑧)𝐾(𝑆), (13) where τ is an employment subsidy to attain the efficient and equitable steady state and 𝑚𝑐(≡ ,) is domestic firm's real marginal cost at time t. Note that the labor hours of each household can be expressed in terms of the terms of trade as 𝐶, 𝑁, =(1−𝜏)𝑚𝑐𝑒𝑥𝑝(𝑧)𝐾(𝑆), (14) where i=U, K. Next, we introduce Calvo-type sticky prices along the lines of Yun (1996). Each domestic firm i infrequently adjust its optimal price 𝑃,(i) with probability (1-α) in any given period, taking 𝑃, and the aggregate demand as given. Since 𝑃,(𝑖) is the same for the reoptimizing firms, i.e., 𝑃,(i) = 𝑃,, the optimal price setting equation can be written as 𝐸󰇩∑𝛼Ξ,, ,𝑌[𝑚𝑐−𝑀 , ,]   󰇪=0, (15) where Ξ,≡𝛽(𝐶.  P)(𝐶. 𝑃) ⁄ and M=   is the average markup in the home goods market. Limited Financial Market Participations and Shocks in Business Cycles in Korea 259 ⓒ 2024 East Asian Economic Review 𝜎,𝜎∗, and 𝜎 in the TANK and RANK models show that the contribution a foreign productivity shock to business cycles in Korea declines in TANK model than in the RANK model before the Asian financial crisis. Table 1. Maximum Likelihood Estimates and Standard Errors (1976:3Q-1997:2Q) Paramete r TAN K Model RAN K Model Estimate Standard Error Estimate Standard Erro r Α 0.7026 0.0416 0.5506 0.0098 Λ 0.2659 0.0085 0 - 𝜌 0.9113 0.0786 0.9957 0.0185 ρ  ∗ 0.9321 0.0456 0.9996 0.0244 𝜌 0.8859 0.0474 0.9816 0.0917 𝜌 0.6462 0.0467 0.6630 0.0072 𝑎 1.4768 0.0539 1.5335 0.0471 𝑎  0.0948 0.0088 0.0000 0. 0095 𝜎 0.0383 0.0030 0.0312 0.0004 𝜎  ∗ 0.0544 0.0043 0.0727 0.0011 𝜎 0.0063 0.0006 0.0062 0.0005 𝜎 0.0250 0.0013 0.1314 0.0615 Η 1.2488 0.0304 1.5172 0.0122 𝐿 -1017.82 𝐿 -1011.99 Note: 𝐿 and 𝐿 denote the maximized value of the TANK and RANK models’ log-likelihood function, respectively. Next, Table 2 displays the decomposition of forecast error variances in detrended output, inflation, the nominal interest rate, and the real exchange rate into components to each of the model's four orthogonal disturbances. The table shows that the domestic productivity shock has dominated in the variations of output at all horizons by accounting for more than 85 percent of unconditional variance of output, while the foreign productivity and monetary policy shocks have played a moderate role in output variations at short horizon. The monetary policy shock has been by far the dominant factor in the fluctuations of inflation at short and medium horizons by accounting for more than 40 percent of the unconditional variance of the inflation rate at the corresponding horizons. The domestic productivity and demand shocks have played an important role in the variations of inflation at all horizons by accounting for 20 percent of the unconditional variance of inflation rate at the corresponding horizons. 260 Yongseung Jung ⓒ Korea Institute for International Economic Policy Table 2. Forecast Error Variance Decompositions (1976:3Q-1997:2Q) Quarters Ahea d Domestic Prod. Shoc k Foreign Prod Shoc k Policy Shoc k Preference Shoc k Output 1 54.2 27.9 14.6 3.3 4 85.1 9.2 4.7 1.0 8 88.2 8.4 2.8 0.6 12 88.2 8.2 2.2 0.5 20 89.4 7.9 2.2 0.5 40 89.3 8.0 2.2 0.5 Inflation 1 2.2 6.2 68.0 23.6 4 18.9 11.4 47.8 21.9 8 24.3 11.9 42.5 21.3 12 26.0 11.7 41.3 21.0 20 26.3 12.1 40.8 20.8 40 25.1 17.8 37.5 19.6 Interest Rate 1 0.1 6.9 18.4 74.6 4 10.5 11.7 5.8 72.0 8 12.8 14.6 3.9 68.7 12 12.9 14.4 3.7 69.0 20 13.8 16.3 3.6 67.3 40 14.6 35.7 2.4 47.3 Exchange rate 1 21.9 74.7 3.4 0.0 22.0 76.9 0.8 0.3 8 21.2 78.0 0.5 0.3 12 20.4 78.9 0.4 0.3 20 19.6 79.7 0.4 0.3 40 19.3 80.0 0.4 0.3 The demand shock has dominated in the behavior of the policy rate during a high economic growth era in Korea. The foreign productivity shock has dominated in the behavior of an international relative price by accounting for more than 75 percent of the unconditional variance of the international relative price at all horizons, while the Limited Financial Market Participations and Shocks in Business Cycles in Korea 261 ⓒ 2024 East Asian Economic Review contribution of the monetary policy shock to the variation of the real exchange rate is nil. Table 3. Maximum Likelihood Estimates and Standard Errors (1998:1Q-2007:2Q) Paramete r TAN K Model RAN K Model Estimate Standard Error Estimate Standard Erro r Α 0.3820 0.1551 0.1644 0.0012 Λ 0.4424 0.0061 0 - 𝜌 0.7825 0.0286 0.8277 0.0113 ρ  ∗ 0.7341 0.0424 0.8955 0.1022 𝜌 0.8471 0.1073 0.9869 0.0319 𝜌 0.0000 0.1669 0.1854 0.0049 𝑎 2.0827 0.1048 2.6509 0.0087 𝑎  0.0004 0.0409 0.0000 0.0122 𝜎 0.0284 0.0071 0.0298 0.0061 𝜎  ∗ 0.1076 0.0137 0.0452 0.0094 𝜎 0.0077 0.0014 0.0090 0.0008 𝜎 0.0140 0.0017 0.1222 0.0204 Η 0.9470 0.0643 0.04880 0.0202 𝐿 -458.7445 𝐿 -434.7973 Note: 𝐿 and 𝐿 denote the maximized value of the TANK and RANK models’ log-likelihood function, respectively. Table 3 presents maximum likelihood estimates of the deep parameters in the second subsample periods, i.e., after the Asian financial crisis, but before the Great Recession, 1998:1Q-2007:2Q. To restore the health of Korean economy hit by the Asian financial crisis, Korea government has implemented some restructuring polices to allow more flexibility in labor market as well as domestic and international financial markets. The market oriented economic policies have increased the share of nonregular or part-time workers and made the housing market as well as the credit market unstable. To deal with the increase in housing prices and credit booms, the government intervened in the housing market with macroprudential tools such as LTV and DTI for the first time to cool down the market. The government’s effort to cool down the housing market and the structural change in the labor market have substantially increased the fraction of households in the second subsample period. The large 262 Yongseung Jung ⓒ Korea Institute for International Economic Policy estimate of λ echoes the prevalence of the negative effect of the unprecedented Asian financial shock intertwined with government’s prudential policy on households. The large estimate of 𝑎 in the interest rate rule shows that the monetary authority implemented an inflation targeting rule to stabilize prices in Korea after the Asian crisis. Since the Korean government was more willing to liberalize capital flows by adopting a flexible exchange rate regime, the Korean economy has been more closely connected with the rest of the world than before. Table 3 indicates that 𝐿=458.75 and 𝐿=434.80, implying that LR=47.9. Since the 0.1 percent critical value for LR is 10.8, the null hypothesis is rejected. Table 4. Forecast Error Variance Decompositions (1998:1Q-2007:2Q) Quarters Ahead Domestic Prod. Shock Foreign Prod Shock Policy Shock Preference Shock Output 1 89.9 9.7 0.2 0.2 4 81.8 17.8 0.1 0.3 8 82.0 17.5 0.1 0.4 12 82.1 17.4 0.1 0.4 20 82.1 17.4 0.1 0.4 40 82.1 17.4 0.1 0.4 Inflation 1 0.8 23.2 59.4 16.6 4 1.4 35.4 37.1 26.1 8 1.5 36.3 33.4 28.8 12 1.6 36.5 32.6 29.3 20 1.6 36.8 32.4 29.2 40 1.6 37.3 32.0 29.1 Interest Rate 1 2.0 57.1 0.0 40.9 4 2.3 56.3 0.0 41.4 8 2.3 54.5 0.0 43.2 12 2.4 54.2 0.0 43.4 20 2.4 54.5 0.0 43.1 40 2.5 54.8 0.0 42.7 Exchange rate 1 4.3 95.5 0.0 0.2 4.8 95.0 0.0 0.2 8 5.0 94.8 0.0 0.2 12 5.1 94.7 0.0 0.2 20 5.1 94.7 0.0 0.2 40 5.1 94.7 0.0 0.2 Limited Financial Market Participations and Shocks in Business Cycles in Korea 263 ⓒ 2024 East Asian Economic Review Table 4 displays the decomposition of forecast error variances in relevant variables into components attributable to each of the model’s orthogonal disturbances. The table shows that the domestic productivity has heavily contributed to output variations at all horizons, and the contribution of the monetary policy shock to output fluctuations is nil during the second subsample period. Table 4 also shows that the effect of the foreign country on the Korean economy has substantially increased as Korea has moved from a managed or pegged exchange rate regime to the flexible exchange rate regime with an inflation targeting rule after the Asian financial crisis. The foreign productivity shock has contributed heavily to the variations of inflation rate and interest rate by accounting for more than 30 percent of the unconditional variance of interest rate and the exchange rate at all horizons. In addition to the dominant role of a monetary policy shock, the preference shock has also contributed to the fluctuation of inflation during the second subsample periods. Since the monetary policy has been conducted to stabilize the price, the effect of a monetary shock on the key macroeconomic variables except inflation is nil as in Table 4. Table 5. Maximum Likelihood Estimates and Standard Errors (2007:3Q-2018:4Q) Paramete r TAN K Model RAN K Model Estimate Standard Error Estimate Standard Erro r α 0.1227 0.0044 0.3189 0.0002 Λ 0.2559 0.0018 0 - 𝜌 0.8964 0.0035 0.9129 0.0089 ρ  ∗ 0.9026 0.0110 0.8993 0.0006 𝜌 0.8565 0.0415 0.7625 0.0016 𝜌 0.3009 0.0120 0.8102 0.0001 𝑎 1.0000 0.0001 1.0102 0.0001 𝑎  0.0025 0.0302 0.1144 0.0006 𝜎 0.0173 0.0025 0.0199 0.0043 𝜎  ∗ 0.0714 0.0153 0.0366 0.0039 𝜎 0.0017 0.0002 0.0007 0.0001 𝜎 0.0017 0.0001 0.0311 0.0003 Η 0.8877 0.0045 0.4703 0.0005 𝐿 -695.69 𝐿 -645.49 Note: 𝐿 and 𝐿 denote the maximized value of the TANK and RANK models’ log-likelihood function, respectively. Table 5 presents maximum likelihood estimates of the deep parameters during the Great Recession, 2007:3Q-2018:4Q. At first glance, the estimate for λ which is comparable to the one in the first sub-sample period might signal that Korea has 264 Yongseung Jung ⓒ Korea Institute for International Economic Policy successfully overcome the Asian financial crisis. But it might be the result of households’ precautionary behavior in the Great Recession. The higher uncertainty about what is going on can force households to cut consumption and save more. The small estimate of the nominal price rigidity α implies that the monetary policy can be ineffective in increasing output at the cost of inflation. Also notice that the monetary policy coefficient 𝑎 implies that there is a one-to-one relationship between a nominal policy rate and the real interest rate near the zero-lower bound. Table 5 indicates that 𝐿=695.59 and 𝐿=645.49, implying that LR=100.2. Since the 0.1 percent critical value for LR is 10.8, the null hypothesis that there is no HtM household in the economy is rejected by the data. Table 6. Forecast Error Variance Decompositions (2007:3Q-2018:4Q) Quarters Ahea d Domestic Prod. Shoc k Foreign Prod Shoc k Policy Shoc k Preference Shoc k Out p ut 1 87.5 12.5 0.0 0.0 4 80.5 19.5 0.0 0.1 8 79.4 20.6 0.0 0.1 12 79.0 21.0 0.0 0.1 20 78.8 21.2 0.0 0.1 40 78.7 21.2 0.0 0.2 Inflation 1 0.3 0.3 87.2 12.2 4 0.4 19.0 66.1 14.5 8 0.4 20.1 64.2 15.3 12 0.6 21.1 63.3 15.0 20 1.2 30.6 54.6 13.6 40 2.1 53.3 34.3 10.3 Interest Rate 1 3.3 1.6 0.6 94.5 4 0.7 54.9 0.1 44.3 8 0.9 55.3 0.1 43.7 12 1.7 56.3 0.1 42.9 20 3.2 67.9 0.1 28.8 40 3.5 82.4 0.0 14.1 Exchan g e rate 1 3.6 96.4 0.0 0.0 3.6 96.4 0.0 0.1 8 3.5 96.5 0.0 0.1 12 3.5 96.5 0.0 0.1 20 3.5 96.5 0.0 0.1 40 3.4 96.6 0.0 0.2 Limited Financial Market Participations and Shocks in Business Cycles in Korea 265 ⓒ 2024 East Asian Economic Review Table 6 displays the decomposition of forecast error variances in relevant variables into components attributable to each of the model’s orthogonal disturbances. First, note that neither a monetary policy shock nor a preference shock is relevant to the variations in output. The domestic productivity shock has been the dominant factor in the variations of output by explaining about 80 percent of the unconditional variance of output at all horizons. The foreign productivity shock has substantially contributed to the fluctuations of output by explaining about 20 percent of output variations. As the monetary authority has tried to boost the aggregate demand by manipulating its policy rate, the effect of a monetary policy shock on the unconditional variance of inflation is larger in the third subsample periods than the ones in the first and second subsample periods at short and medium horizons. The foreign productivity shock has played an important role in the variations of inflation and interest rates, in addition to the fluctuation of the international relative price. Notice that the contrition of a monetary policy shock to the variations of other relevant variables is nil, implying that the monetary policy is ineffective to boost the economy with very low interest rate, i.e., near the zero-lower bound. Figure 2. Impulse Response Function to a Domestic Productivity Shock Notes: The lines with circles, the lines with stars, and the dotted lines display the response of selected variables to a one-standard deviation of positive domestic productivity innovation in the first subperiods (1976:3Q-1997:2Q), the second sub-periods (1998:1Q-2007:2Q), and the third sub-periods (2007:3Q-2018:3Q). 266 Yongseung Jung ⓒ Korea Institute for International Economic Policy Figure 2 displays the impulse response function of some selected variables to a positive domestic productivity shock. The circle lines ( ), the star lines ( ), and the dotted lines ( ) denote the response of relevant variables to the shock in the first, second, and the third subsample periods, respectively. The real exchange rate depreciates to the positive domestic productivity shock with the expansion of domestic output. The strong increase in output entails a fall of inflation rate to the shock in the first subsample period, which induces the monetary authority to cut its interest rate to stabilize the price as in Figure 1. However, a moderate expansion of output to the positive domestic productivity shock generates muted inflation, which induces the monetary authority to mildly adjust its policy rate in the second and third subsample periods. Notice that there is a very mild variation during the third sub-period, wherein the policy rate is near the zero-lower bound during the Great Recession period.2 Figure 3. Impulse Response Function to a Foreign Productivity Shock Notes: The lines with circles, the lines with stars, and the dotted lines display the response of selected variables to a one-standard deviation of positive foreign productivity innovation in the first subperiods (1976:3Q-1997:2Q), the second sub-periods (1998:1Q-2007:2Q), and the third sub-periods (2007:3Q-2018:3Q). 2 To get some intuition on the relevance of the TANK model over the business cycle in Korea, I have added impulse response functions of the RANK model in the appendix. Limited Financial Market Participations and Shocks in Business Cycles in Korea 267 ⓒ 2024 East Asian Economic Review Figure 3 presents the impulse response function of some selected variables to the foreign productivity shock in the first, second, and third subsample periods. The effect of foreign productivity shock on output is milder than the effect of domestic productivity shock, but its effect on the real exchange rate is much larger than the effect of the domestic productivity shock since the foreign output entails a proportional change in the international relative price through the risk-sharing condition. After the Asian financial crisis with the financial liberalization in Korea, the effect of foreign productivity shock on the Korean economy has been stronger than before the Asian financial crisis. Figure 4. Impulse Response Function to a Preference Shock Notes: The lines with circles, the lines with stars, and the dotted lines display the response of selected variables to a one-standard deviation of positive domestic preference innovation in the first subperiods (1976:3Q-1997:2Q), the second sub-periods (1998:1Q-2007:2Q), and the third sub-periods (2007:3Q-2018:3Q). Figure 4 displays the impulse response function of some selected variables to the domestic preference productivity shock in the relevant subsample periods. The positive impact of domestic demand shock on output is expansionary during the first subsample period, while its effect on domestic economy activity is mild in the second 268 Yongseung Jung ⓒ Korea Institute for International Economic Policy and third sample sub-periods wherein the boosting effect of domestic demand shock has been limited with the financial liberalization in Korea. Figure 5. Impulse Response Function to an Interest Rate Shock Notes: The lines with circles, the lines with stars, and the dotted lines display the response of selected variables to a one-standard deviation of negative domestic interest innovation in the first subperiods (1976:3Q-1997:2Q), the second sub-periods (1998:1Q-2007:2Q), and the third sub-periods (2007:3Q-2018:3Q). Figure 5 shows the impulse response function of an interest rate shock to the selected variables. There are stronger responses of relevant variables to the shock in the first subsample period than in the second and third subsample periods. The muted response of output and inflation associated with a mild increase of the policy rate during the second and third subsample periods displays that the monetary authority has successfully conducted its policy to stabilize the economy with an adoption of the inflation targeting rule after the Asian financial crisis. V. Concluding Remarks This paper specifies a simple two-agent small open economy new Keynesian model with incomplete financial market, and then investigates the role of HtM households in