Author: Martin Gaynor
Publisher:
ISBN:
Category : Incentives in industry
Languages : en
Pages : 32
Book Description
Recent work has shown that, in the presence of moral hazard, balanced budget Nash equilibria in groups are not pareto-optimal. This work shows that when agents misperceive the effects of their actions on the joint outcome, there exist a set of sharing rules which balance the budget and lead to a pareto-optimal Nash equilibria. Journal of Economic Literature, Classification Numbers: 022, 026, 511.
Misperceptions, Moral Hazard, and Incentives in Groups
Author: Martin Gaynor
Publisher:
ISBN:
Category : Incentives in industry
Languages : en
Pages : 32
Book Description
Recent work has shown that, in the presence of moral hazard, balanced budget Nash equilibria in groups are not pareto-optimal. This work shows that when agents misperceive the effects of their actions on the joint outcome, there exist a set of sharing rules which balance the budget and lead to a pareto-optimal Nash equilibria. Journal of Economic Literature, Classification Numbers: 022, 026, 511.
Publisher:
ISBN:
Category : Incentives in industry
Languages : en
Pages : 32
Book Description
Recent work has shown that, in the presence of moral hazard, balanced budget Nash equilibria in groups are not pareto-optimal. This work shows that when agents misperceive the effects of their actions on the joint outcome, there exist a set of sharing rules which balance the budget and lead to a pareto-optimal Nash equilibria. Journal of Economic Literature, Classification Numbers: 022, 026, 511.
Journal of Institutional and Theoretical Economics
"Money's Worth" of Social Security
Author: United States. Congress. Senate. Committee on Finance
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 160
Book Description
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 160
Book Description
Journal of Economic Literature
Error Components in Grouped Data
Author: William T. Dickens
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 48
Book Description
When estimating linear models using grouped data researchers typically weight each observation by the group size. Under the assumption that the regression errors for the underlying micro data have expected values of zero, are independent and are homoscedastic, this procedure produces best linear unbiased estimates. This note argues that for most applications in economics the assumption that errors are independent within groups is inappropriate. Since grouping is commonly done on the basis of common observed characteristics, it is inappropriate to assume that there are no unobserved characteristics in common. If group members have unobserved characteristics in common, individual errors will be correlated. If errors are correlated within groups and group sizes are large then heteroscedasticity may be relatively unimportant and weighting by group size may exacerbate heteroscedasticity rather than eliminate it. Two examples presented here suggest that this may be the effect of weighting in most non-experimental applications. In many situations unweighted ordinary least squares may be a preferred alternative. For those cases where it is not, a maximum likelihood and an asymptotically efficient two-step generalized least squares estimator are proposed. An extension of the two-step estimator for grouped binary data is also presented.
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 48
Book Description
When estimating linear models using grouped data researchers typically weight each observation by the group size. Under the assumption that the regression errors for the underlying micro data have expected values of zero, are independent and are homoscedastic, this procedure produces best linear unbiased estimates. This note argues that for most applications in economics the assumption that errors are independent within groups is inappropriate. Since grouping is commonly done on the basis of common observed characteristics, it is inappropriate to assume that there are no unobserved characteristics in common. If group members have unobserved characteristics in common, individual errors will be correlated. If errors are correlated within groups and group sizes are large then heteroscedasticity may be relatively unimportant and weighting by group size may exacerbate heteroscedasticity rather than eliminate it. Two examples presented here suggest that this may be the effect of weighting in most non-experimental applications. In many situations unweighted ordinary least squares may be a preferred alternative. For those cases where it is not, a maximum likelihood and an asymptotically efficient two-step generalized least squares estimator are proposed. An extension of the two-step estimator for grouped binary data is also presented.
New Econometric Techniques for Macroeconomic Policy Evaluation
Author: John B. Taylor
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 114
Book Description
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 114
Book Description
Competition and Quality in Health Care Markets
Author: Martin Gaynor
Publisher: Now Publishers Inc
ISBN: 1601980078
Category : Business & Economics
Languages : en
Pages : 83
Book Description
Provides an economic assessment of the impact of competition on quality in health care markets. This book offers performance standards for competition; findings from economic theory; and, empirical evidence on health care competition and quality.
Publisher: Now Publishers Inc
ISBN: 1601980078
Category : Business & Economics
Languages : en
Pages : 83
Book Description
Provides an economic assessment of the impact of competition on quality in health care markets. This book offers performance standards for competition; findings from economic theory; and, empirical evidence on health care competition and quality.
Errors in Variables in Panel Data
Author: Zvi Griliches
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 50
Book Description
Panel data based on various longitudinal surveys have become ubiquitous in economics in recent years. Estimation using the analysis of covariance approach allows for control of various "individual effects" by estimation of the relevant relationships from the "within" dimension of the data. Quite often, however, the "within" results are unsatisfactory, "too low" and insignificant. Errors of measurement in the independent variables whose relative importance gets magnified in the within dimension are often blamed for this outcome. However, the standard errors-in-variables model has not been applied widely, partly because in the usual micro data context it requires extraneous information to identify the parameters of interest. In the panel data context a variety of errors-in-variables models may be identifiable and estimable without the use of external instruments. We develop this idea and illustrate its application in a relatively simple but not uninteresting case: the estimation of "labor demand" relationships, also known as the "short run increasing returns to scale" puzzle.
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 50
Book Description
Panel data based on various longitudinal surveys have become ubiquitous in economics in recent years. Estimation using the analysis of covariance approach allows for control of various "individual effects" by estimation of the relevant relationships from the "within" dimension of the data. Quite often, however, the "within" results are unsatisfactory, "too low" and insignificant. Errors of measurement in the independent variables whose relative importance gets magnified in the within dimension are often blamed for this outcome. However, the standard errors-in-variables model has not been applied widely, partly because in the usual micro data context it requires extraneous information to identify the parameters of interest. In the panel data context a variety of errors-in-variables models may be identifiable and estimable without the use of external instruments. We develop this idea and illustrate its application in a relatively simple but not uninteresting case: the estimation of "labor demand" relationships, also known as the "short run increasing returns to scale" puzzle.
Testing the Random Walk Hypothesis
Author: Robert J. Shiller
Publisher:
ISBN:
Category : Random walks (Mathematics)
Languages : en
Pages : 28
Book Description
Power functions of tests of the random walk hypothesis versus stationary first order autoregressive alternatives are tabulated for samples of fixed span but various frequencies of observation.
Publisher:
ISBN:
Category : Random walks (Mathematics)
Languages : en
Pages : 28
Book Description
Power functions of tests of the random walk hypothesis versus stationary first order autoregressive alternatives are tabulated for samples of fixed span but various frequencies of observation.
Implementing Causality Tests with Panel Data, with an Example from Local Public Finance
Author: Douglas Holtz-Eakin
Publisher:
ISBN:
Category : Finance, Public
Languages : en
Pages : 58
Book Description
Publisher:
ISBN:
Category : Finance, Public
Languages : en
Pages : 58
Book Description