SEMIPARAMETRIC EFFICIENCY BOUNDS FOR CONDITIONAL MOMENT RESTRICTION MODELS WITH DIFFERENT CONDITIONING VARIABLES

2015 ◽  
Vol 32 (4) ◽  
pp. 917-946 ◽  
Author(s):  
Marian Hristache ◽  
Valentin Patilea
Keyword(s):  
Regression Models ◽  
Supply And Demand ◽  
Simultaneous Equations ◽  
Conditional Moment ◽  
Efficient Score ◽  
Semiparametric Efficiency ◽  
Regression Quantile ◽  
New Applications ◽  
Theoretical Results ◽  
Moment Restriction

This paper addresses the problem of semiparametric efficiency bounds for conditional moment restriction models with different conditioning variables. We characterize such an efficiency bound, that in general is not explicit, as a limit of explicit efficiency bounds for a decreasing sequence of unconditional (marginal) moment restriction models. An iterative procedure for approximating the efficient score when this is not explicit is provided. Our theoretical results provide new insight for the theory of semiparametric efficiency bounds literature and open the door to new applications. In particular, we investigate a class of regression-like (mean regression, quantile regression,…) models with missing data, an example of a supply and demand simultaneous equations model and a generalized bivariate dichotomous model.

scholarly journals CONDITIONAL MOMENT RESTRICTIONS IN CENSORED AND TRUNCATED REGRESSION MODELS

2001 ◽  
Vol 17 (5) ◽  
pp. 863-888 ◽  
Author(s):  
Whitney K. Newey
Keyword(s):  
Regression Models ◽  
Efficient Estimation ◽  
Truncated Regression ◽  
Conditional Moment ◽  
Weighted Version ◽  
Unknown Distribution ◽  
Consistent Estimators ◽  
Semiparametric Efficiency Bound ◽  
Moment Restrictions ◽  
Moment Restriction

Censored and truncated regression models with unknown distribution are important in econometrics. This paper characterizes the class of all conditional moment restrictions that lead to √n-consistent estimators for these models. The semiparametric efficiency bound for each conditional moment restriction is derived. In the case of a nonzero bound it is shown how an estimator can be constructed and that an appropriately weighted version can attain the efficiency bound. These estimators also work when the disturbance is independent of the regressors. The paper discusses combining conditional moment restrictions for more efficient estimation in this case.

Multivariate Simultaneous Generalized ARCH

1995 ◽  
Vol 11 (1) ◽  
pp. 122-150 ◽  
Author(s):  
Robert F. Engle ◽  
Kenneth F. Kroner
Keyword(s):  
Sufficient Conditions ◽  
Likelihood Estimation ◽  
Positive Definiteness ◽  
Covariance Matrices ◽  
Simultaneous Equations ◽  
Equivalence Relations ◽  
Conditional Covariance ◽  
Arch Models ◽  
Necessary And Sufficient ◽  
Theoretical Results

This paper presents theoretical results on the formulation and estimation of multivariate generalized ARCH models within simultaneous equations systems. A new parameterization of the multivariate ARCH process is proposed, and equivalence relations are discussed for the various ARCH parameterizations. Constraints sufficient to guarantee the positive definiteness of the conditional covariance matrices are developed, and necessary and sufficient conditions for covariance stationarity are presented. Identification and maximum likelihood estimation of the parameters in the simultaneous equations context are also covered.

scholarly journals A NOTE ON GENERALIZED EMPIRICAL LIKELIHOOD ESTIMATION OF SEMIPARAMETRIC CONDITIONAL MOMENT RESTRICTION MODELS

2016 ◽  
Vol 33 (5) ◽  
pp. 1242-1258 ◽  
Author(s):  
Naoya Sueishi
Keyword(s):  
Empirical Likelihood ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Unknown Parameters ◽  
Conditional Moment ◽  
Finite Dimensional ◽  
Dimensional Parameters ◽  
Image Position ◽  
Asymptotically Efficient ◽  
Moment Restriction

This paper proposes an empirical likelihood-based estimation method for semiparametric conditional moment restriction models, which contain finite dimensional unknown parameters and unknown functions. We extend the results of Donald, Imbens, and Newey (2003, Journal of Econometrics 117, 55–93) by allowing unknown functions to be included in the conditional moment restrictions. We approximate unknown functions by a sieve method and estimate the finite dimensional parameters and unknown functions jointly. We establish consistency and derive the convergence rate of the estimator. We also show that the estimator of the finite dimensional parameters is $\sqrt n$-consistent, asymptotically normally distributed, and asymptotically efficient.

CONSISTENT MODEL SPECIFICATION TESTS

2000 ◽  
Vol 16 (6) ◽  
pp. 1016-1041 ◽  
Author(s):  
Yanqin Fan ◽  
Qi Li
Keyword(s):  
Nonparametric Tests ◽  
Model Specification ◽  
Local Alternatives ◽  
Exponential Weight ◽  
Conditional Moment ◽  
Specification Tests ◽  
Consistent Model ◽  
Close Relationship ◽  
Complex Valued ◽  
Theoretical Results

We point out the close relationship between the integrated conditional moment tests in Bierens (1982, Journal of Econometrics 20, 105–134) and Bierens and Ploberger (1997, Econometrica 65, 1129–1152) with the complex-valued exponential weight function and the kernel-based tests in Härdle and Mammen (1993, Annals of Statistics 21, 1926–1947), Li and Wang (1998, Journal of Econometrics 87, 145–165), and Zheng (1996, Journal of Econometrics 75, 263–289). It is well established that the integrated conditional moment tests of Bierens (1982) and Bierens and Ploberger (1997) are more powerful than kernel-based nonparametric tests against Pitman local alternatives. In this paper we analyze the power properties of the kernel-based tests and the integrated conditional moment tests for a sequence of “singular” local alternatives, and show that the kernel-based tests can be more powerful than the integrated conditional moment tests for these “singular” local alternatives. These results suggest that integrated conditional moment tests and kernel-based tests should be viewed as complements to each other. Results from a simulation study are in agreement with the theoretical results.

scholarly journals Development of Supply and Demand Functions of Pakistan’s Wheat Crop

2010 ◽  
Vol 15 (1) ◽  
pp. 91-102 ◽  
Author(s):  
Muhammad Zulfiqar ◽  
Anwar F. Chishti
Keyword(s):  
Side Population ◽  
Supply And Demand ◽  
National Level ◽  
Simultaneous Equations ◽  
Wheat Crop ◽  
Supply Side ◽  
Market Forces ◽  
Demand Side ◽  
Domestic Consumption ◽  
Demand Functions

A simultaneous-equations model was used to capture the supply and demand functions for Pakistan’s wheat sector at the national level. This model reflects the fact that Pakistan’s domestic wheat supply is priceresponsive and positively affected by the use of nutrient fertilizers. While price appears to be a statistically significant factor on the supply side, it is statistically insignificant on the demand side. Population size appears to be very significant in determining wheat demand. The wheat import supply seems to be influenced by the current world wheat price, current world wheat supplies, Pakistan’s domestic consumption in previous years, and domestic supply in previous years. We recommend that policymakers allow market forces to play a role in the wheat economy in a way that protects producers from adverse market conditions. The availability of various nutrient fertilizers should be central to policies on future inputs use. Work is also needed on wheat alternatives so that the country’s dependence on wheat is eased as much as possible.

scholarly journals Analysis of inflation management model factors as regards supply and demand

Ekonomika ◽  
2016 ◽  
Vol 95 (1) ◽  
pp. 43-63
Author(s):  
Dainius Butautas
Keyword(s):  
Human Capital ◽  
Content Analysis ◽  
Regression Models ◽  
Supply And Demand ◽  
Labour Productivity ◽  
Pair Correlation ◽  
Government Expenditure ◽  
Demand And Supply ◽  
General Government ◽  
Linear Correlation Analysis

This article analyses the demand and supply aspects of the determinants of CPI inflation in Lithuania in 1998–2008. Content analysis was used to identify and group significant demand and supply inflation factors and using RGT, objectively assess and generalize the results. Pair linear correlation analysis confirmed the significance for CPI inflation of the factors identified through content analysis, and both research methods reliably and effectively helped to identify factors for regression models of inflation. Content analysis revealed that the causes of inflation most often mentioned and traditionally regarded as significant in the economic literature are factors such as money and wages, capital, competition and monopolies, and so on. Pair correlation research showed the significance for inflation of supply and demand factors such as income distribution, income levels, taxes, saving, human capital and labour productivity as well as exports and imports – things which content analysis gave only average or little mention. Regression models confirmed and helped to concretize the significance for inflation of the identified demand and supply factors. The results of the research show that inconsistent monetary and general government expenditure policies reinforce private consumption and capital shocks. Note that human capital and employment, which changed little during the analysed period, did not show the large significance for inflation that they are commonly thought to have.

scholarly journals Constrained conditional moment restriction models

2015 ◽  
Author(s):  
Victor Chernozhukov ◽  
Whitney K. Newey ◽  
Andres Santos
Keyword(s):  
Conditional Moment ◽  
Moment Restriction
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