41 research outputs found
The impact of government size on economic growth: a threshold analysis
We examine the nature of the relationship between government size and economic growth and identify the optimal level of government size using a large dataset through a novel and very general non-linear panel Generalized Method of Moments approach. We show that this relationship is statistically significant above and below the optimal level, even after splitting our sample to developed and developing countries. Finally, we find an asymmetric impact of government size on economic growth in both developed and developing countries around the estimated threshold
Multiple Structural Breaks in Interactive Effects Panel Data and the Impact of Quantitative Easing on Bank Lending
This paper develops a new toolbox for multiple structural break detection in
panel data models with interactive effects. The toolbox includes tests for the
presence of structural breaks, a break date estimator, and a break date
confidence interval. The new toolbox is applied to a large panel of US banks
for a period characterized by massive quantitative easing programs aimed at
lessening the impact of the global financial crisis and the COVID--19 pandemic.
The question we ask is: Have these programs been successful in spurring bank
lending in the US economy? The short answer turns out to be: ``No''
Threshold Regression in Heterogeneous Panel Data with Interactive Fixed Effects
This paper introduces unit-specific heterogeneity in panel data threshold
regression. Both slope coefficients and threshold parameters are allowed to
vary by unit. The heterogeneous threshold parameters manifest via a
unit-specific empirical quantile transformation of a common underlying
threshold parameter which is estimated efficiently from the whole panel. In the
errors, the unobserved heterogeneity of the panel takes the general form of
interactive fixed effects. The newly introduced parameter heterogeneity has
implications for model identification, estimation, interpretation, and
asymptotic inference. The assumption of a shrinking threshold magnitude now
implies shrinking heterogeneity and leads to faster estimator rates of
convergence than previously encountered. The asymptotic theory for the proposed
estimators is derived and Monte Carlo simulations demonstrate its usefulness in
small samples. The new model is employed to examine the Feldstein-Horioka
puzzle and it is found that the trade liberalization policies of the 80's
significantly impacted cross-country capital mobility.Comment: 25 pages, 1 figur
Generalized �Fixed-T Panel Unit Root Tests Allowing for Structural Breaks
In this paper we suggest panel data unit root tests which allow for a structural breaks in the individual
effects or linear trends of panel data models. This is done under the assumption that the disturbance
terms of the panel are heterogeneous and serially correlated. The limiting distributions of the suggested
test statistics are derived under the assumption that the time-dimension of the panel (T) is �fixed, while
the cross-section (N) grows large. Thus, they are appropriate for short panels, where T is small. The
tests consider the cases of a known and unknown date break. For the latter case, the paper gives the
analytic form of the distribution of the test statistics. Monte Carlo evidence suggest that our tests have
size which is very close to its nominal level and satisfactory power in small-T panels. This is true even
for cases where the degree of serial correlation is large and negative, where single time series unit root
tests are found to be critically oversized
The Power Performance of Fixed-T Panel Unit Root Tests allowing for Structural Breaks
The asymptotic local power of least squares based fixed-T panel unit root tests allowing for a structural break in their individual effects and/or incidental trends of the AR(1) panel data model is studied. These tests correct the least squares estimator of the autoregressive coefficient of this panel data model for its inconsistency due to the individual effects and/or incidental trends of the panel. The limiting distributions of the tests are analytically derived under a sequence of local alternatives, assuming that the cross-sectional dimension of the tests (N) grows large. It is shown that the considered fixed-T tests have local power which tends to unity fast only if the panel data model includes individual effects. For panel data models with incidental trends, the power of the tests becomes trivial. However, this problem does not always appear if the tests allow for serial correlation of the error term
The Power Performance of Fixed-T Panel Unit Root Tests allowing for Structural Breaks
The asymptotic local power of least squares based fixed-T panel unit root tests allowing for a structural break in their individual effects and/or incidental trends of the AR(1) panel data model is studied. These tests correct the least squares estimator of the autoregressive coefficient of this panel data model for its inconsistency due to the individual effects and/or incidental trends of the panel. The limiting distributions of the tests are analytically derived under a sequence of local alternatives, assuming that the cross-sectional dimension of the tests (N) grows large. It is shown that the considered fixed-T tests have local power which tends to unity fast only if the panel data model includes individual effects. For panel data models with incidental trends, the power of the tests becomes trivial. However, this problem does not always appear if the tests allow for serial correlation of the error term
Optimal versus realized bank credit risk and monetary policy
Standard banking theory suggests that there exists an optimal level of credit risk that yields maximum bank profit. We identify the optimal level of risk-weighted assets that maximizes banks’ returns in the full sample of US banks over the period 1996–2011. We find that this optimal level is cyclical, being higher than the realized credit risk in relatively stable periods with high profit opportunities for banks but quickly decreasing below the realized in periods of turmoil. We place this cyclicality into the nexus between bank risk and monetary policy. We show that a contractionary monetary policy in stable periods, where the optimal credit risk is higher than the realized credit risk, increases the gap between them. An increase in this gap also comes as a result of an expansionary monetary policy in bad economic periods, where the realized risk is higher than the optimal risk
On the Local Power of Fixed T Panel Unit Root Tests with Serially Correlated Errors
Analytical asymptotic local power functions are employed to study the effects of general form short term serial correlation on �fixed-T panel data unit root tests. Two
models are considered, one that has only individual intercepts and one that has both individual intercepts and individual trends. It is shown that tests based on IV estimators are more powerful in all cases examined. Even more, for the model with individual trends an IV based test is shown to have non-trivial local power at the natural root-N rate