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Effect of Monetary Policy on Government Spending Multiplier

  • Jong-Suk Han and Joonyoung Hur EMAIL logo
Published/Copyright: May 3, 2022
The B.E. Journal of Macroeconomics
From the journal The B.E. Journal of Macroeconomics Volume 23 Issue 1

Abstract

This paper empirically examines the effect of monetary policy on the government spending multiplier when the nominal interest rate is not bound to zero. We estimate a time-varying coefficient vector autoregressive (TVC-VAR) model using 2000:Q1 to 2019:Q3 quarterly data of Korea, whose policy rate is distant from zero. We find a substantial degree of time variation in the medium-run government spending multipliers, which increase over time and become statistically different from zero throughout the 2010s. Yet the reverse pattern is observed in the policy rate responses to government spending shocks, decreasing gradually until 2008–09 and then stagnating for the subsequent period. Decompositions of the policy rate responses reveal that inflation is an important ingredient in determining the responses of the nominal interest rate to government spending shocks, and thus has a critical impact on the size of government spending multipliers. In particular, our finding underscores a substantial role of the monetary policy stance against inflation in shaping government spending multipliers.

Keywords: government spending multiplier; monetary policy; time-varying coefficient VAR
JEL Classification: C11; E32; E62; E52
Corresponding author: Joonyoung Hur, School of Economics, Sogang University, 35, Baekbeom-ro, Mapo-gu, Seoul 04107, Republic of Korea, E-mail:

Acknowledgments

We would like to thank Felipe Schwartzman (the associate editor) and an anonymous referee, whose comments were particularly helpful. We are grateful to Jinill Kim, Soyoung Kim, Jong-Wha Lee and Kwanho Shin for valuable discussions and comments. We also thank seminar participants from the Bank of Korea’s Research Department, Korea Development Institute, Korea Institute for International Economic Policy, Korea Institute of Public Finance, Korea University, and Yonsei University for helpful comments.

Appendix A: Data

We employ Korean data from 1990:Q1 to 2019:Q3 for the endogenous variables of the VAR models. Our VAR specifications also include four exogenous variables which use quarterly data for the growth rate of oil prices, the federal funds rate, US real GDP per capita, and the real exchange rate against the dollar. Detailed data descriptions are as follows:

Government Spending  = log ( Domestic Real Per Capita Government Spending ) , GDP  = log ( Domestic Real Per Capita GDP ) , Consumption  = log ( Domestic Real Per Capita Consumption ) , Investment = log ( Domestic Real Per Capita Investment ) , Inflation Rate = log ( Domestic CPI/Domestic CPI ( − 1 ) ) × 100 , Taxes  = log ( Domestic Real Per Capita Taxes ) , Nominal Interest Rate  = Domestic Overnight Call Rate , Growth Rate of Oil Price = log ( Oil Price/Oil Price ( − 1 ) ) × 100 , US Nominal Interest Rate = US Federal Funds Rate , US GDP = log ( US Real Per Capita GDP ) , Real Exchange Rate  = Nominal Exchange Rate  ( won/dollar ) × US CPI/Domestic CPI .

The original data and their sources are given as follows:

  1. Domestic Nominal Government Spending: Total government spending expenditure, not seasonally adjusted / Source: Korean Statistical Information Service (KOSIS)

  2. Domestic Real GDP: Real gross domestic product, seasonally adjusted / Source: The Bank of Korea’s Economic Statistics System Database (BOK-ECOS)

  3. Domestic Real Consumption: Real gross private consumption expenditure, seasonally adjusted / Source: BOK-ECOS

  4. Domestic Real Investment: Real gross fixed capital formation, seasonally adjusted / Source: BOK-ECOS

  5. Domestic CPI: Consumer price indexes, 2015=100, seasonally adjusted / Source: BOK-ECOS

  6. Domestic Nominal Taxes: Total tax revenue, not seasonally adjusted / Source: KOSIS

  7. Domestic Nominal Interest Rate: Overnight call rate, uncollateralized, percent per annum, averages of daily figures / Source: BOK-ECOS

  8. Domestic Population: Total population, annual / Source: KOSIS

  9. Oil Price: Global price of Dubai Crude, US dollars per barrel, quarterly, not seasonally adjusted / Source: Federal Reserve Economic Data (FRED, St. Louis Fed), Series ID “POILDUBUSDM”

  10. US Federal Funds Rate: Averages of daily figures, percent / Source: Board of Governors of the Federal Reserve System

  11. US Real GDP: Real gross domestic product, chained dollars, billions of chained (2009) dollars, seasonally adjusted at annual rates / Source: NIPA Table 1.1.6, Line 1

  12. Nominal Exchange Rate: Won/dollar exchange rate / Source: BOK-ECOS

  13. US CPI: Consumer price index for all urban consumers, all items, index 1982–1984 = 100, quarterly, seasonally adjusted / Source: FRED, Series ID “CPIAUCSL”

  14. US Population: Civilian noninstitutional population, ages 16 years and over, seasonally adjusted / Source: US Department of Labor, Bureau of Labor Statistics

B. Additional Results (Not for Publication)

This appendix provides additional results not included in the paper.

B.1 Actual Impulse Responses and the Summation of ψ t 4 , k ’s

This section compares the actual impulse responses of the nominal interest rate to government spending shocks (Figure 6) and the summation of the ψ t 4 , k terms, ∑ k = 1 4 ψ t 4 , k , as in (14) in the main text. As mentioned in Section 4.2, ∑ k = 1 4 ψ t 4 , k is defined to approximate the nominal interest rate to government spending shocks. In this regard, this comparison is to demonstrate the size of the approximation error. The results are provided in Figure A1.

Figure A1: Time-varying impulse responses of the interest rate to 1% increases in government spending for selected horizons associated with the baseline 4-variable TVC-VAR model (solid line with shaded area) and the summation of ψ t 4 , k ${\psi }_{t}^{4,k}$ ’s ( ∑ k = 1 4 ψ t 4 , k ${\sum }_{k=1}^{4}{\psi }_{t}^{4,k}$ , thick and thin dashed lines). The y-axis is in percentage.
Figure A1:

Time-varying impulse responses of the interest rate to 1% increases in government spending for selected horizons associated with the baseline 4-variable TVC-VAR model (solid line with shaded area) and the summation of ψ t 4 , k ’s ( ∑ k = 1 4 ψ t 4 , k , thick and thin dashed lines). The y-axis is in percentage.

As the figure shows, these two objectives seem to be somewhat different in size. This tendency, however, is attenuated as the horizon increases, which can be rationalized by the fact that the summation is associated with the lagged VAR coefficients up to three quarters. More importantly, the summation of ψ t 4 , k ’s displays a similar time-varying pattern to the actual impulse responses.

B.2 Robustness: Controlling for Taxes

This section provides a robustness check by augmenting the model with taxes. The first subsection discusses the effect of government shocks on macroeconomic variables, whereas the second subsection conducts the counterfactual experiments in Section 5 with taxes.

B.2.1 Effect of Government Spending Shocks with Taxes

We specify a 5-variable VAR system consisting of government spending, output, inflation, taxes and the nominal interest rate. Notice that this set of variables is the one employed in Perotti (2005) and Caldara and Kamps (2008) for evaluating the efficacy of government spending in stimulating output. Following Caldara and Kamps (2008), the identification of government spending shocks relies on the recursive ordering as listed above. Ordering taxes after output and inflation can be rationalized by the fact that, given the tax rate, the tax base is contemporaneously affected by these two variables, and thus tax receipts change.

Focusing first on the impulse responses of taxes, two findings emerge from Figure A2. First, the impulse responses of taxes are not statistically different from zero for most of the periods and horizons considered. Second, although not statistically significant, tax responses exhibit a slight upward tendency over time in terms of the median estimates. This finding is universal to all the considered horizons.

Figure A2: Time-varying impulse responses of taxes to 1% increases in government spending for selected horizons associated with the 5-variable TVC-VAR model augmented with taxes. In each panel, median and 68% band estimates are reported. The y-axis is in percentage.
Figure A2:

Time-varying impulse responses of taxes to 1% increases in government spending for selected horizons associated with the 5-variable TVC-VAR model augmented with taxes. In each panel, median and 68% band estimates are reported. The y-axis is in percentage.

Figure A3 plots the present-value multiplier estimates for selected horizons associated with the 5-variable (dotted lines) and baseline 4-variable (solid line with shaded area) VAR specifications. Overall, the impulse responses from the 5-variable model display slightly wider band estimates than those from the baseline 4-variable VARs, which is observed more clearly for longer horizons. This tendency may be attributable to the “curse of dimensionality” problem typically associated with TVC-VAR models in which the number of parameters to be estimated increases rapidly with additional model variables. The longer-run multipliers tend to become slightly bigger under the 5-variable system, and the difference stands out more for the beginning of the sample period. It is nonetheless worth noting that controlling for taxes does not alter substantially the time-varying pattern of the government spending multiplier estimates.

Figure A3: Time-varying present-value multipliers for selected horizons, associated with the 4-variable baseline TVC-VAR model (solid line with shaded area) and with the 5-variable TVC-VAR model augmented with taxes (dotted lines). In each panel, median and 68% band estimates are reported. The y-axis is in Korean won.
Figure A3:

Time-varying present-value multipliers for selected horizons, associated with the 4-variable baseline TVC-VAR model (solid line with shaded area) and with the 5-variable TVC-VAR model augmented with taxes (dotted lines). In each panel, median and 68% band estimates are reported. The y-axis is in Korean won.

Figure A4: Time-varying present-value multipliers for selected horizons, associated with the 5-variable TVC-VAR model augmented with taxes (solid line with shaded area) and with the 4-variable TVC-VAR model without the nominal interest rate (dotted lines). In each panel, median and 68% band estimates are reported. The y-axis is in Korean won.
Figure A4:

Time-varying present-value multipliers for selected horizons, associated with the 5-variable TVC-VAR model augmented with taxes (solid line with shaded area) and with the 4-variable TVC-VAR model without the nominal interest rate (dotted lines). In each panel, median and 68% band estimates are reported. The y-axis is in Korean won.

B.2.2 Comparison to the 4-variable Model without the Nominal Interest Rate

For a robustness check, we estimate a model with taxes, but without the nominal interest rate, and compare the results to those of the baseline 4-variable specification. The results, which are the 5-variable VAR model counterparts of Figure 10, are depicted in Figure A4. In addition, Figure A5 reports the 5-variable model results analogous to Figure 11. These figures show that the main findings of the paper are unlikely to be altered by adding taxes to the model.

Figure A5: [Upper panels] Differences between the time-varying present-value multipliers for selected horizons associated with the 4-variable TVC-VAR model without the nominal interest rate and 5-variable TVC-VAR model augmented with taxes, along with the sum of the inflation coefficients in the nominal interest rate equation multiplied by the corresponding Cholesky factors associated with the 5-variable TVC-VAR model augmented with taxes. In each panel, median and 68% band estimates are reported. [Lower panels] Scatter plots for the median sums of the inflation coefficients in the nominal interest rate equation multiplied by the corresponding Cholesky factors (x-axis) and median differences between the time-varying present-value multipliers (y-axis). In each panel, the solid line indicates the fitted values of the linear OLS regression.
Figure A5:

[Upper panels] Differences between the time-varying present-value multipliers for selected horizons associated with the 4-variable TVC-VAR model without the nominal interest rate and 5-variable TVC-VAR model augmented with taxes, along with the sum of the inflation coefficients in the nominal interest rate equation multiplied by the corresponding Cholesky factors associated with the 5-variable TVC-VAR model augmented with taxes. In each panel, median and 68% band estimates are reported. [Lower panels] Scatter plots for the median sums of the inflation coefficients in the nominal interest rate equation multiplied by the corresponding Cholesky factors (x-axis) and median differences between the time-varying present-value multipliers (y-axis). In each panel, the solid line indicates the fitted values of the linear OLS regression.

B.3 Government Spending Impulse Responses for Selected Dates

Figure A6 plots the impulse responses of government spending to 1% initial increases in government spending for selected dates.

Figure A6: Impulse responses of government spending to 1% initial increases in government spending for selected dates associated with the TVC-VAR model. In the left 6 panels, median (solid line) and 68% band (shaded area) estimates are reported, while median estimates across various dates are plotted in the right panel. The y-axis is in percentage.
Figure A6:

Impulse responses of government spending to 1% initial increases in government spending for selected dates associated with the TVC-VAR model. In the left 6 panels, median (solid line) and 68% band (shaded area) estimates are reported, while median estimates across various dates are plotted in the right panel. The y-axis is in percentage.

B.4 Alternative Ordering of the Variables

Given the recursive ordering scheme used to identify government spending shocks in this paper, it may be the case that the response of the interest rate to inflation can be different for alternative orderings, especially between output and the inflation rate. Accordingly, we check whether the results are robust when an alternative ordering between output and inflation is considered. To this end, we estimate a model with inflation ordered ahead of output such that the entire ordering structure of the alternative specification is given as follows: government spending first, inflation second, output third, and the nominal interest rate last.

Figure A7 plots the present-value multiplier estimates that emerge from the model with the alternative ordering, together with those from the baseline specification. Figures A8 and A9 show how the impulse responses of inflation and the nominal interest rate vary depending upon the alternative ordering. All these figures indicate that the results change very little when the alternative ordering is used instead. The impulse responses associated with both orderings look quite alike, as they show a similar pattern of time variation.

Figure A7: Time-varying present-value multipliers for selected horizons, associated with the baseline 4-variable TVC-VAR model (solid line with shaded area) and with the 4-variable TVC-VAR model with the alternative ordering of output and inflation (dotted lines). In each panel, median and 68% band estimates are reported. The y-axis is in Korean won.
Figure A7:

Time-varying present-value multipliers for selected horizons, associated with the baseline 4-variable TVC-VAR model (solid line with shaded area) and with the 4-variable TVC-VAR model with the alternative ordering of output and inflation (dotted lines). In each panel, median and 68% band estimates are reported. The y-axis is in Korean won.

Figure A8: Time-varying impulse responses of inflation to 1% increases in government spending for selected horizons associated with the baseline 4-variable TVC-VAR model. In each panel, median (solid line) and 68% band (shaded area) estimates are reported. The y-axis is in percentage.
Figure A8:

Time-varying impulse responses of inflation to 1% increases in government spending for selected horizons associated with the baseline 4-variable TVC-VAR model. In each panel, median (solid line) and 68% band (shaded area) estimates are reported. The y-axis is in percentage.

Figure A9: Time-varying impulse responses of the interest rate to 1% increases in government spending for selected horizons associated with the baseline 4-variable TVC-VAR model. In each panel, median (solid line) and 68% band (shaded area) estimates are reported. The y-axis is in percentage.
Figure A9:

Time-varying impulse responses of the interest rate to 1% increases in government spending for selected horizons associated with the baseline 4-variable TVC-VAR model. In each panel, median (solid line) and 68% band (shaded area) estimates are reported. The y-axis is in percentage.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/bejm-2020-0229).

Received: 2020-10-19
Revised: 2022-01-12
Accepted: 2022-04-14
Published Online: 2022-05-03

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Advances
  3. A New General Equilibrium Welfare Measure, with Application to Labor Income Taxes
  4. Labor Share Dynamics and Factor Complementarity
  5. Effect of Monetary Policy on Government Spending Multiplier
  6. News-Driven Housing Booms: Spain Versus Germany
  7. Sovereign Debt Crisis, Fiscal Consolidation, and Active Central Bankers in a Monetary Union
  8. Housing Taxation and Economic Growth: Analysis of a Balanced-Growth Model with Residential Capital
  9. Intergenerational Linkages, Uncertain Lifetime and Educational and Health Expenditures
  10. Contributions
  11. Tolerance of Informality and Occupational Choices in a Large Informal Sector Economy
  12. Uncertainty Shocks, Innovation, and Productivity
  13. Asymmetric Effects of Private Debt on Income Growth
  14. Interpreting Structural Shocks and Assessing Their Historical Importance
  15. Charge-offs, Defaults and the Financial Accelerator
  16. Filtering Persistent and Asymmetric Cycles
  17. Population Aging and Convergence of Household Credit
  18. Robustly Optimal Monetary Policy in a Behavioral Environment
  19. Forward Guidance Effectiveness in a New Keynesian Model with Housing Frictions
  20. The Welfare Effects of Social Insurance Reform in the Presence of Intergenerational Transfers
https://doi.org/10.1515/bejm-2020-0229
Keywords for this article
government spending multiplier; monetary policy; time-varying coefficient VAR

Articles in the same Issue

  1. Frontmatter
  2. Advances
  3. A New General Equilibrium Welfare Measure, with Application to Labor Income Taxes
  4. Labor Share Dynamics and Factor Complementarity
  5. Effect of Monetary Policy on Government Spending Multiplier
  6. News-Driven Housing Booms: Spain Versus Germany
  7. Sovereign Debt Crisis, Fiscal Consolidation, and Active Central Bankers in a Monetary Union
  8. Housing Taxation and Economic Growth: Analysis of a Balanced-Growth Model with Residential Capital
  9. Intergenerational Linkages, Uncertain Lifetime and Educational and Health Expenditures
  10. Contributions
  11. Tolerance of Informality and Occupational Choices in a Large Informal Sector Economy
  12. Uncertainty Shocks, Innovation, and Productivity
  13. Asymmetric Effects of Private Debt on Income Growth
  14. Interpreting Structural Shocks and Assessing Their Historical Importance
  15. Charge-offs, Defaults and the Financial Accelerator
  16. Filtering Persistent and Asymmetric Cycles
  17. Population Aging and Convergence of Household Credit
  18. Robustly Optimal Monetary Policy in a Behavioral Environment
  19. Forward Guidance Effectiveness in a New Keynesian Model with Housing Frictions
  20. The Welfare Effects of Social Insurance Reform in the Presence of Intergenerational Transfers
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