Irina B. Panovska

State-dependent effects of fiscal policy

We investigate the effects of government spending on US output with a threshold structural vector autoregressive model. We consider Bayesian model comparison and generalized impulse response analysis to test for nonlinearities in the responses of output to government spending. Our empirical findings support state-dependent effects of fiscal policy, with the government spending multiplier larger and more persistent whenever there is considerable economic slack. Based on capacity utilization as the preferred threshold variable, the estimated multiplier is large (1.6) for a low-utilization regime that accounts for more than half of the sample observations from 1967 to 2012 according to the estimated threshold level.

What Explains the Recent Jobless Recoveries

This paper considers a correlated unobserved-components model for output, employment, and hours in order to disentangle the causes for the last three jobless recoveries. The composition of the structural shocks during recessions and the periods immediately following recessions has changed, as have the responses of employment and hours to those shocks. Recessions before 1984 were followed by recoveries driven by positive permanent shocks to output, whereas post-1984 recessions were followed by weak recoveries in demand. Employment is more sensitive to demand shocks post-1984, leading to weak recoveries in employment. In addition, hours and employment were complements before 1984, but are treated as substitutes after 1984. Much of the initial decrease in demand is now absorbed on the intensive margin.

Testing Stationarity with Unobserved Components Models

In the aftermath of the global financial crisis, competing measures of the trend in macroeconomic variables such as US real GDP have featured prominently in policy debates. A key question is whether the large shocks to macroeconomic variables will have permanent effects—i.e., in econometric terms, do the data contain stochastic trends? Unobserved components models provide a convenient way to estimate stochastic trends for time series data, with their existence typically motivated by stationarity tests that allow for at most a deterministic trend under the null hypothesis. However, given the small sample sizes available for most macroeconomic variables, standard Lagrange multiplier tests of stationarity will perform poorly when the data are highly persistent. To address this problem, we propose the use of a likelihood ratio test of stationarity based directly on the unobserved components models used in estimation of stochastic trends. We demonstrate that a bootstrap version of this test has far better small-sample properties for empirically-relevant data generating processes than bootstrap versions of the standard Lagrange multiplier tests. An application to US real GDP produces stronger support for the presence of large permanent shocks when using the likelihood ratio test as compared to the standard tests.

Is Business Cycle Asymmetry Intrinsic in Industrialized Economies

We consider a model-averaged forecast-based estimate of the output gap to measure economic slack for ten industrialized economies. Our measure takes changes in the long-run growth rate into account and, by accounting for model uncertainty using equal weights on different forecast-based estimates, is robust to different assumptions about the underlying structure of the economy. For each country, we find that the estimated output gap is highly asymmetric, with much larger negative movements during recessions than positive movements in expansions, suggesting that this particular form of business cycle asymmetry is an intrinsic characteristic of industrialized economies. Furthermore, the estimated output gap is strongly negatively correlated with future output growth and unemployment and positively correlated with capacity utilization in each case. It also implies a convex Phillips Curve in many cases.

When Do Discretionary Changes in Government Spending or Taxes Have Larger Effects

We investigate the effects of discretionary changes in government spending and taxes using a medium-scale nonlinear vector autoregressive model with policy shocks identified via sign restrictions. Tax cuts and spending increases have larger stimulative effects when there is excess slack in the economy, while they are much less effective, especially in the case of government spending increases, when the economy is close to potential. We find that contractionary shocks have larger effects than expansionary shocks across the business cycle, but this is much more pronounced during deep recessions and sluggish recoveries than in robust expansions. Notably, tax increases are highly contractionary and largely self-defeating in reducing the debt-to-GDP ratio when the economy is in a deep recession. The effectiveness of discretionary government spending, including its state dependence, appears to be almost entirely due to the response of consumption. The responses of both consumption and investment to discretionary tax changes are state dependent, but investment plays the larger quantitative role.