Franklin

On the Properties of Various Estimators for Fiscal Reaction Functions [electronic resource] Celasun, Oya.

Author/Creator:
Celasun, Oya.
Publication:
Washington, D.C. : International Monetary Fund, 2006.
Series:
IMF eLibrary
IMF Working Papers; Working Paper No. 06/182.
IMF Working Papers; Working Paper No. 06/182
Format/Description:
Government document
Book
1 online resource (29 p.)
Local subjects:
Budget constraint.
Budget deficits.
Coefficient vector.
Correlation.
Correlations.
Debt.
Debt Management.
Deficit.
Domestic debt.
Dummy variables.
Dynamic models.
Econometrics.
Economic models.
Equation.
Equations.
Estimation of equation.
Fiscal authorities.
Fiscal balance.
Fiscal balances.
Fiscal behavior.
Fiscal debt.
Fiscal effort.
Fiscal policy.
Fiscal reaction.
Fiscal reaction function.
Fiscal reaction functions.
Fiscal studies.
Functional form.
Models with Panel Data.
Monte carlo simulations.
Normal distribution.
Outliers.
Primary fiscal balance.
Probability.
Public debt.
Random variable.
Sample size.
Samples.
Standard deviation.
Standard errors.
Time series.
Brazil.
Grenada.
United Kingdom.
Summary:
This paper evaluates the bias of the least-squares-with-dummy-variables (LSDV) method in fiscal reaction function estimations. A growing number of studies estimate fiscal policy reaction functions-that is, relationships between the primary fiscal balance and its determinants, including public debt and the output gap. A previously unexplored methodological issue in these estimations is that lagged debt is not a strictly exogenous variable, which biases the LSDV estimator in short panels. We derive the bias analytically to understand its determinants and run Monte Carlo simulations to assess its likely size in empirical work. We find the bias to be smaller than the bias of the LSDV estimator in a comparable autoregressive dynamic panel model and show the LSDV method to outperform a number of alternatives in estimating fiscal reaction functions.
Notes:
Description based on print version record.
Contributor:
Celasun, Oya.
Kang, Joong Shik.
Other format:
Print Version:
ISBN:
1451864426:
9781451864427
ISSN:
1018-5941
Publisher Number:
10.5089/9781451864427.001
Access Restriction:
Restricted for use by site license.
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