This paper investigates the long-run effects of public debt and inflation on economic growth. Our contribution is both theoretical and empirical. On the theoretical side, we develop a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in dynamic...

This paper investigates the long-run effects of public debt and infl ation on economic growth. Our contribution is both theoretical and empirical. On the theoretical side, we develop a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in dynamic...

A broad empirical literature uses “event study” research designs for treatment effect estimation, a setting in which all units in the panel receive treatment but at random times. We make four novel points about identification and estimation of causal effects in this setting and show their...

This paper investigates the long-run effects of public debt and inflation on economic growth. Our contribution is both theoretical and empirical. On the theoretical side, we develop a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in dynamic...

This paper estimates the long run elasticity of the demand for fixed nonresidential capital (both equipment and structures) to changes in its user cost using a quarterly panel of two-digit manufacturing data from South Africa from 1970 to 2001. Using a difference specification that does not rely...

Monetary policy rule parameters estimated with conventional estimation techniques can be severely biased if the estimation sample includes periods of low interest rates. Nominal interest rates cannot be negative, so that censored regression methods like Tobit estimation have to be used to...

This paper empirically investigates the relationship between real money demand, real income, interest rates and real consumption. The paper provide a mixed strategy for estimating the money demand function that incorporates shifting from a system of equations vector auto regression (VAR)...

We estimate location values for single family houses using a standard house price and characteristics dataset and local polynomial regressions (LPR), a procedure that allows for complex interactions between the values of structural characteristics and the value of land. We also compare LPR to...

As an alternative to ordinary least squares (OLS), we estimate location values for single family houses using a standard housing price and characteristics dataset by local polynomial regressions (LPR), a semi-parametric procedure. We also compare the LPR and OLS models in the Denver metropolitan...

Since little is known about the degree of bias in estimated fixed effects in panel data models, we run Monte Carlo simulations on a range of different estimators. We find that Anderson-Hsiao IV, Kiviet's bias-corrected LSDV and GMM estimators all perform well in both short and long panels....