Dualism and cross-country growth regressions

This paper develops empirical growth models suitable for dual economies, and studies the relationship between structural change and economic growth. Changes in the structure of employment will raise aggregate productivity when the marginal product of labor varies across sectors. The models in the paper incorporate this effect in a more flexible way than previous work. Estimates of the models imply sizeable marginal product differentials, and indicate that the reallocation of labor makes a significant contribution to the international variation in productivity growth.     

Specification and sensitivity analysis of cross-country growth regressions

We compare the sensitivity analysis of cross-country growth regressions based on extreme bounds analysis to a more direct specification testing approach using non-nested hypotheses tests. The results suggest that those specifications that are adequate are also those that include two of the only few conditioning variables that are found to be robust, namely the standard deviation of inflation and the standard deviation of domestic credit. First Version Received: November 2000/Final Version Received: May 2001     

A Monte Carlo study of growth regressions

Using Monte Carlo simulations, this paper evaluates the bias properties of estimators commonly used to estimate growth regressions derived from the Solow model. We explicitly allow for measurement error, country-specific fixed effects and regressor endogeneity. An OLS estimator applied to a single cross-section of variables averaged over time (the between estimator) performs best in terms of the extent of bias on each of the estimated coefficients. Fixed-effects and the Arellano–Bond GMM estimator overstate the speed of convergence under a wide variety of assumptions, while the between estimator understates it. Finally, fixed effects and Arellano–Bond bias towards zero the slope estimates on the human and physical capital accumulation variables, while the between estimator and the Blundell–Bond system GMM estimator bias these coefficients upwards.      

A non-linear sensitivity analysis of cross-country growth regressions

We extend the sensitivity analysis of cross-country growth regressions of Levine and Renelt (1992) by introducing a semi-parametric formulation of their regression function. Our results differ from theirs in how certain policy variables affect growth rates. We find that distortion variables, such as the standard deviation of gross domestic credit and inflation and real exchange rate distortions, have a robust negative effect on growth. JEL Classification: O47, C14
Une analyse de sensibilité non-linéaire des régressions de croissance pour divers pays. Les auteurs utilisent une formulation semi-paramétrique des équations de croissance de Levine et Renelt (1992) pour divers pays afin de rendre leur analyse de sensibilité plus compréhensive. Les résultats different de ceux de Levine et Renelt en ce que certaines variables de politique affectent les taux de croissance. On découvre que certains facteurs comme l'écart type du crédit intérieur brut et de l'inflation, et des distorsions des taux de change réels, ont un effet négatif important sur la croissance.     

Discrete and smooth switching regressions for Australian labour productivity growth

One of the potential hazards in empirical wok is structural instability. In the simple case where the change from one reime to another is instananeous the analyst can resort to switching regressions after idetifying the offending break. However, what if the transition is gradual, rather than discrete, and takes time to complete? This paper offers a suitable modification of the switching regression model and illustrates how this more general technique can handle smooth transitions when estimating the growth of Australian labour productivity.     

Cross-country growth regressions: problems of heterogeneity,stability and interpretation

The paper discusses the issues of heterogeneity and stability of cross-country growth regressions that have been used to study the problem of convergence. Almost all studies use pooled regressions. The paper considers the issue of pooling under heterogeneity using a hierarchical Bayesian method and estimates growth regressions for different panels studied in earlier papers, and different regimes. The conclusion is that the convergence rates are higher than those obtained from pooled regressions under the assumption of homogeneity and that there is instability over time in the relationships.     

Aggregation and the Endogeneity Problem

This paper investigates the combined effects of the aggregation and endogeneity problems when there exists a correlation between explanatory variables and the error term in the micro equation. Comparing OLS estimates on the basis of an asymptotic-square-bias criterion, the analysis indicates that aggregate equations are in general subject to less endogeneity due to the synchronization effect. The trade-off between aggregation and endogeneity biases is examined and the conditions under which the aggregate equation is superior to the micro equation are derived in terms of the relative sizes of parameters. [210]     

Maximum entropy regressions

Maximum entropy (ME) regression is compared to ordinary regression in the case of two observations on two normally distributed variables (one dependent and one explanatory) with correlation coefficient ρ. ME regressions have the smaller risk under quadratic loss if ? lies in the interval ±0.95. In the case of two explanatory variables and two observations, ordinary regression is not possible but ME regressions do exist and have finite risk.     

Excess bias and the nature of budget growth

To examine the hypothesis that budget growth has been excessive, the concept of ‘correct’ budget size must first be defined. This proves a difficult task for the level of public services, but especially so regarding redistribution and transfer payments. Next, potential sources of bias are explored, including distortions in voting, bureaucracy and political leadership. Analysis shows that bias may be in either direction, making for deficient as well as excess budgets. Institutional reform, therefore, should not prejudge the outcome by imposing limitations. The goal should be to improve the budget process, however this may affect budget size.     

Endogeneity in Semiparametric Binary Response Models

This paper develops and implements semiparametric methods for estimating binary response (binary choice) models with continuous endogenous regressors. It extends existing results on semiparametric estimation in single-index binary response models to the case of endogenous regressors. It develops a control function approach to account for endogeneity in triangular and fully simultaneous binary response models. The proposed estimation method is applied to estimate the income effect in a labour market participation problem using a large micro data-set from the British Family Expenditure Survey. The semiparametric estimator is found to perform well, detecting a significant attenuation bias. The proposed estimator is contrasted to the corresponding probit and linear probability specifications.     

Endogeneity and sample selection in a model for remittances

We estimate a remittance model in which we address endogeneity and reverse causality relationships between immigrants' remittances, pre-transfer income and consumption. In order to take into account the fact that a large share of individuals do not remit, instrumental variable variants of the double-hurdle and Heckit selection models are proposed and estimated by Limited Information ML; semiparametric extensions are considered as robustness checks. Our results for a sample of recent immigrants to Australia show that endogeneity is substantial and that estimates obtained by the methods previously employed in the literature may be misleading if given a behavioral interpretation.     

Spurious regressions with stationary series

A spurious regression occurs when a pair of independent series, but with strong temporal properties, are found apparently to be related according to standard inference in an OLS regression. Although this is well known to occur with pairs of independent unit root processes, this paper finds evidence that similar results are found with positively autocorrelated autoregressive series or long moving averages. This occurs regardless of the sample size and for various distributions of the error terms.     

Resolving spurious regressions and serially correlated errors

This study investigates the spurious regression phenomenon for two independent stationary and non-stationary processes and illustrates, using a Monte Carlo analysis, that estimation of the spurious regression in first differences or with a lagged dependent variable eliminates the spurious regression problem. Moreover, the results also apply in eliminating the problem of serially correlated errors as well as the problem of ARCH(1) errors.     

Parameter constancy in cointegrating regressions

This paper proposes an approach to testing for coefficient stability in cointegrating regressions in time series models. The test statistic considered is the one-sided version of the Lagrange Multiplier (LM) test. Its limit distribution is non-standard but is nuisance parameter free and can be represented in terms of a stochastic bridge process which is tied down like a Brownian bridge but relies on a random rather than a deterministic fraction to do so. The approach provides a test of the null hypothesis of cointegration against specific directions of departure from the null; subset coefficient stability tests are also available. A small simulation studies the size and power properties of these tests and an empirical illustration to Australian data on consumption, disposable income, inflation and money is provided.     

On the Endogeneity of the Mean-Variance Efficient Frontier

The endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in the portfolio selection literature and in widely used textbooks. The authors demonstrate this endogeneity and discuss the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual assets.     

基于内生性视角的人民币国际化研究

当前人民币国际化优势与劣势并存。中国经济实力和综合国力增强,金融机构国际地位提升,人民币公信力提高,人民币国际化环境改善等,使得人民币国际化具有占优条件。另一方面,金融市场不够发达,资本项目较低的开放度,人民币不能够自由兑换,又使得人民币处于国际货币竞争劣势。从货币国际化竞争条件内生性理论来看,需要动态看待人民币国际化条件：随着人民币国际化的推进,将一定程度上促进人民币国际竞争条件的改善。中国应采取分步实施策略、同步推进金融市场与人民币国际化进程、促进贸易发展和提高综合国力、＂两个平行金融市场＂制度推进金融市场建设、完善人民币汇率形成机制、加强区域合作等有效措施,改善人民币国际化竞争条件。     

Testing linear and log-linear regressions with autocorrelated errors

This paper considers the problem of testing linear and log-linear models with autocorrelated errors. Test of functional form as well as functional form and autocorrelation simultaneously are obtained using the Lagrange multiplier approach.     

Spurious regressions driven by excessive volatility

This paper shows that the excessive volatility results in spurious regressions. The spuriousness can be driven by persistency in the error variances unlike the conventional spurious regressions that are generated by the persistency in the level of regression errors.     

贸易开放与经济增长的内生性研究新进展

关于贸易开放和经济增长的关系在经济学界一直存在分歧,尤其表现在Rodriguez和Rodrik(2000)的评论中。在过去的十年中,数据的丰富和数据质量的提高,新的工具变量的发现以及新的计量方法的运用,使得该领域成为国际经济学的热点领域之一。本文首先介绍了贸易开放的内生性表现,然后从工具变量法、倍差法、配对法和其他识别方法等四个部分展开介绍近年来在这些领域中控制贸易开放的内生性方法,重点关注新的工具变量的构造。应用这些控制内生性方法的研究表明,贸易对于人均收入具有显著地正效应,并且实证结果具有稳健性。全球化对收入的总体影响中,约有一半的效应是来自于纯粹的货物贸易的影响,另一半是来自于全球化的其他因素,如自然人的流动、FDI等。寻找贸易开放的时变的工具变量是该领域未来研究的一个方向。