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Record Nr. |
UNINA9910959814203321 |
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Autore |
Celasun Oya |
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Titolo |
On the Properties of Various Estimators for Fiscal Reaction Functions / / Oya Celasun, Joong Kang |
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Pubbl/distr/stampa |
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Washington, D.C. : , : International Monetary Fund, , 2006 |
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ISBN |
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9786613820983 |
9781462311460 |
1462311466 |
9781452723907 |
1452723907 |
9781282447783 |
1282447785 |
9781451989007 |
1451989008 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (29 p.) |
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Collana |
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Altri autori (Persone) |
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Soggetti |
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Fiscal policy - Econometric models |
Finance, Public |
Bonds |
Debt Management |
Debt |
Debts, Public |
Econometric models |
Econometrics & economic statistics |
Econometrics |
Economic theory |
Estimation techniques |
Estimation |
Fiscal Policy |
Fiscal policy |
Fiscal stance |
General Financial Markets: General (includes Measurement and Data) |
Investment & securities |
Investments: Bonds |
Macroeconomics |
Macroeconomics: Production |
National Deficit Surplus |
Output gap |
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Panel Data Models |
Production and Operations Management |
Production |
Public debt |
Public finance & taxation |
Public Finance |
Sovereign Debt |
Spatio-temporal Models |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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""Contents""; ""I. INTRODUCTION""; ""II. BIASES OF ORDINARY-LEAST-SQUARES (OLS) AND LEAST-SQUARES-WITH-DUMMY VARIABLES ( LSDV) ESTIMATORS: ANALYTICAL SOLUTIONS""; ""III. MONTE CARLO EXPERIMENTS""; ""IV. CONCLUSION""; ""References"" |
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Sommario/riassunto |
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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. |
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