Abstract
This paper studies the dynamic effects of the fiscal policy shock on private activity using an array of vector autoregressive models for the post-war U.S. data. We are particularly interested in the role of consumer sentiment in the transmission of fiscal stimulus. Our major findings are as follows. Private spending fails to rise persistently in response to government spending shocks, while they exhibit persistent and significant increases when the sentiment shock occurs. Employing not only linear but also nonlinear state-dependent VAR model estimations, we show that the government spending shock generates consumer pessimism in all phases of business cycle resulting in subsequent decreases in private activity, which ultimately weakens the effectiveness of the fiscal policy. Our counterfactual simulation exercises confirm the important role of sentiment in propagating fiscal stimulus to private spending.
Acknowledgment
An earlier version of this paper was circulated under the title “Government Spending Shocks and Private Acitity: The Role of Sentiments”. Our thanks go to seminar/conference participants at Xi’an Jiaotong University, Keio University, Bank of Korea, KEA International Conference, and Southern Economic Association Meetings. Special thanks go to Masao Ogaki, Ippei Fujiwara, Randy Beard, and Henry Thompson for helpful comments. The views expressed in this paper are those of the authors and do not reflect the official policy or position of the NYC Department of Environmental Protection, or the U.S. Government.
Unit root test results.
| ADF t | pv | Lag | |
|---|---|---|---|
| TGDP | −2.099 | 0.245 | 2 |
| PGDP | −1.794 | 0.384 | 2 |
| SENT (CS) | −3.420 | 0.010 | 4 |
| SENE (CSE) | −3.575 | 0.007 | 0 |
| SENC (CSC) | −3.909 | 0.002 | 4 |
| FC & I | −0.090 | 0.249 | 4 |
| TC & I | −1.818 | 0.372 | 4 |
| DEFN | −2.774 | 0.062 | 4 |
| SC & I | −2.366 | 0.151 | 4 |
| FGOV | −1.833 | 0.365 | 4 |
| TGOV | −2.304 | 0.171 | 4 |
-
We report the augmented Dickey–Fuller (ADF) test statistics (ADF t ) with an intercept along with their associated p-values (pv). The optimal number of lags was chosen by the general to specific rule with a maximum of 4 lags. The ADF test fails to reject the null of nonstationarity for all variables at the 5% significance level with exceptions of the index of consumer expectations (CSE) and the index of current economic conditions (CSC).
Stationarity of the VAR.
| VAR | Intercept | Intercept and trend |
|---|---|---|
| FGOV-GDP-SENT | 0.994 | 0.970 |
| FGOV-PGDP-SENT | 0.994 | 0.976 |
| FC & I-GDP-SENE | 0.993 | 0.953 |
| FC & I-PGDP-SENE | 0.993 | 0.950 |
-
We report the modulus of the largest eigenvalue of the tri-variate VAR(4). The ordering of the VAR does not matter because eigenvalues are calculated from the reduced form VAR.
Some survey of consumers data.
We obtained these time series data, the index of consumer Opinions about Government’s Economic Policy and the Expected change in Real income during the next Year, from University of Michigan’s survey of consumers. Shaded areas indicate NBER recession dates.
Modulus graphs of the eigenvalues of the VAR.
We provide sample modulus graphs of the eigenvalues of the VAR. The first one corresponds to the model (GDP-SENE-FC&I) of Bachmann and Sims (2012), accompanied by the graph below when the VAR is demeaned and detrended. The modulus graphs in the second column are from the VAR with the private GDP. The red circle indicates the unit circle.
![Figure A3:
Bachmann and Sim’s (2012) model with alternative specifications
x
t
=
f
c
&
i
t
,
sent
t
,
gdp
t
′
${\mathbf{x}}_{t}={\left[fc\& {i}_{t},\enspace {\text{sent}}_{t},{\text{gdp}}_{t}\right]}^{\prime }$
.
The first figure replicates the nonlinear response function estimates from the VAR model in Bachmann and Sims (2012) using their code and the data, FC&I, SENE, and GDP from 1960:I to 2011:IV. The solid line represents the output response to the government spending shock during economic recessions, while the dashed line is the response during booms. Note that responses are qualitatively similar when the VAR includes both the intercept and time trend. We thank Eric Sims for generously sharing the code and the data that were used in Bachmann and Sims (2012).](/document/doi/10.1515/bejm-2020-0198/asset/graphic/j_bejm-2020-0198_fig_011.jpg)
Bachmann and Sim’s (2012) model with alternative specifications
The first figure replicates the nonlinear response function estimates from the VAR model in Bachmann and Sims (2012) using their code and the data, FC&I, SENE, and GDP from 1960:I to 2011:IV. The solid line represents the output response to the government spending shock during economic recessions, while the dashed line is the response during booms. Note that responses are qualitatively similar when the VAR includes both the intercept and time trend. We thank Eric Sims for generously sharing the code and the data that were used in Bachmann and Sims (2012).
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