金融发展、技术进步与区域经济增长——基于欠发达地区的分析

运用向量自回归模型(VAR)估计区域金融发展水平与全要素生产率之间的关系考察金融发展与区域经济增长之间的技术进步影响,并运用格兰杰因果检验对区域金融发展规模与全要素生产率增长率之间的因果关系做出检验。研究发现,1990年以来中国西北各省区的经济金融化程度均得到提高,但是金融发展对全要素生产率的影响较弱,全要素生产率对金融规模的响应程度和显著性不高,西北地区金融发展对经济增长的作用还没有得到充分的发挥。     

Do Financial and Institutional Variables Enhance the Impact of Remittances on Economic Growth in Latin America and the Caribbean? A Panel Cointegration Analysis

Using recently developed panel unit root and panel cointegration tests and the Fully-Modified OLS methodology (FMOLS), this paper estimates the impact of remittances on the economic growth of selected upper and lower income Latin American & Caribbean (LAC) countries over the 1990–2007 period. Despite the large flow of remittances to the region, there have been relatively few empirical studies assessing the impact of remittances on economic growth in LAC. Panel unit root tests suggest that several of the macro variables included in the model exhibit unit roots, yet, at the same time, Pedroni’s panel cointegration test determined that there is a cointegrating relationship among the variables in the estimated model. The FMOLS estimates suggest that remittances have a positive and significant effect on economic growth in both groups of countries. The estimates also indicate that both the degree of economic freedom and credit provided by the banking system have a positive and significant effect on economic growth in upper (middle) income LAC countries. The sign of the interaction term between remittances and the credit (and EFI) variables suggest that remittances act as substitutes for these variables. Finally, the effect of remittances on both sets of countries is stronger in the presence of a financial (credit) variable.     

The value of birth control

The attempt was made to obtain an improved estimate of the economic value of birth control programs in developing countries. A medium sized econometric simulation model -- based on data covering a cross-section of 67 countries -- was constructed to investigate the implications to a developing economy of birth prevention. Fertility measures were included in the model as important endogenous variables in the economic process, and parameter values were supplied by formal estimation rather than expert judgment. A matrix of age-specific birth and survival rates was used. The model has sufficient detail to generate a complete age distribution for the population, yielding improved estimates of the value of birth control and other growth policies. Initial focus is on the construction of the model. This is followed by simulation of the system with simulated paths compared to observed paths for a few countries. Projections of real per capita output and other variables with and without the presence of a birth control program are presented. The size of the differential economic effect associated with lower fertility is examined for 17 sets of initial conditions corresponding to a selection of 17 developing countries. Comparisons of birth control with other forms of investment are made.     

Unveiling covariate inclusion structures in economic growth regressions using latent class analysis

We propose the use of Latent Class Analysis methods to analyze the covariate inclusion patterns across specifications resulting from Bayesian model averaging exercises. Using Dirichlet Process clustering, we are able to identify and describe dependency structures among variables in terms of inclusion in the specifications that compose the model space. We apply the method to two datasets of potential determinants of economic growth. Clustering the posterior covariate inclusion structure of the model space formed by linear regression models reveals interesting patterns of complementarity and substitutability across economic growth determinants.     

The limited usefulness of macroeconomic Bayesian VARs when estimating the probability of a US recession

The Bayesian VAR model provides a convenient tool for generating predictive densities and making probability statements regarding the future development of economic variables. This paper investigates the usefulness of standard macroeconomic Bayesian VAR models to estimate the probability of a US recession. Defining a recession as two quarters in a row of negative GDP growth, the probability is estimated for two quarters of the most recent US recession, namely 2008Q3–2008Q4. In contrast to judgemental probabilities from this point in time, it is found that the BVAR assigns a very low probability to such an event. This is true also when survey data, which generally are considered as good leading indicators, are included in the models. We conclude that while Bayesian VAR models are good forecasting tools in many cases, the results in this paper raise question marks regarding their usefulness for predicting recessions.     

SHORT-CUT ESTIMATES OF REAL INCOME

The United Nations International Comparisons Project (ICP) has conducted in-depth purchasing-power parity (PPP) studies of the so-called "benchmark" countries (of which there were 34 in the 1975 sample). In the absence of PPP studies of the rest of the countries in the world, the ICP team has constructed "short-cut" estimates of real income (that is, income converted from domestic currency to dollars at PPP) for the nonbenchmark countries. The idea of a "short-cut" procedure for estimating real income is to run a regression of real income on nominal income (that is, income converted from domestic currency to dollars at a market exchange rate) and other variables among the benchmark countries and then to use this regression to estimate real income for the nonbenchmark countries. The most recent ICP short-cut estimates have been based on regressions of real income on nominal income and the foreign trade ratio. The present study expands the list of candidate variables that might be included in a short-cut regression. The list includes educational attainments, the share of minerals in GDP, the trade balance, the growth of the money supply, tourist receipts, and the share of nontradables in GDP. The theory underlying the inclusion of each of these variables is discussed. Regressions are run with various combinations of these variables and some short-cut estimates of real income for 76 market economies are presented.     

新疆存在“资源诅咒”吗

基于国内各省区经济增长和资源丰裕度的统计考察,构造新疆经济增长与资源丰裕度、技术、制度、物质积累等变量的回归模型。检验发现,新疆自然资源对经济增长的负影响存在一期滞后,制度因素对新疆经济增长起着举足轻重的作用。     

Research & development and growth: A Bayesian model averaging analysis

We examine the effect of research and development (R&D) on long-term economic growth using the Bayesian model averaging (BMA) to deal rigorously with model uncertainty. Previous empirical studies, which applied BMA, investigated the effect of dozens of regressors on long-term growth, but they did not examine the effect of R&D due to data unavailability. We extend these studies by proposing to capture the investment in R&D by the number of Nobel prizes in science. Using our indicator, the estimates show that R&D exerts a positive effect on long-term growth. This result is robust to many different parameter and model prior structures as well as to alternative definitions of R&D indicator.     

A demand and supply analysis of productivity growth

The paper rejects growth accounting as failing to reveal the economic forces that drive growth. Instead, it seeks to explain changing productivity growth in terms of economic phenomena such as the changing structure of output, the rate of adoption of new technology, and the strength of aggregrate demand. We introduce such a model and test it using pooled cross section and time series data for 16 OECD economies over a 30 year period. The parameter estimates allow us to decompose each economy's productivity growth into the part caused by its changing structure and the part explained by demand conditions. The estimates are used to account for the productivity slowdown that occurred in these economies after 1973, and to examine the recent productivity increase in the US. The model fully explains this growth surge in terms of the changed demand factors and structure of the US economy. We conclude by arguing that a prime benefit of strong aggregate demand is its stimulation of investment and technological change, leading to the adoption of new technology on a broad front.     

CULTURE AND GROWTH: SOME EMPIRICAL EVIDENCE

Using Hofstede's cultural data set, this paper examines the impact of cultural characteristics on a nation's economic performance. Using a two‐step estimation procedure, we first estimate a panel growth regression and obtain estimates of each nation's fixed effects, which reflect idiosyncratic differences in growth performance. In the second step, we regress the fixed effects on invariant cultural and institutional variables. Our estimation results suggest that individuality and tolerance for uncertainty are the most important cultural factors in explaining nation‐specific growth performance. Furthermore, our findings suggest that political and property rights play a major role in determining idiosyncratic growth.     

Searching for the Fed’s reaction function

There is still some doubt about those economic variables that really matter for the Fed’s decisions. In comparison with other estimations, this study uses the approach of Bayesian model averaging (BMA). The estimations show that over the long-run inflation, unemployment rates and long-term interest rates are the crucial variables in explaining the Federal Funds Rate. In the other two estimation samples, also the fiscal deficit and monetary aggregates were of relevance. There is also evidence for interest rate smoothing. In addition, we account for parameter instability by combining BMA with time-varying coefficient (TVC) modelling. We find strong evidence for structural breaks. Finally, a model average is constructed via an TVC-BMA approach.     

Inter-Region Transportation Costs,Regional Economic Growth,and Disparities in China

To examine the correlation between regional economic growth and inter-region transportation costs in China, this study establishes a regional economic growth model embedded with inter-region transportation costs based on the Cobb-Douglas production function. Based on a balanced growth empirical model, this study verifies the correlation by conducting a regression analysis of the panel data of 29 provinces, municipalities, and autonomous regions from 1985 to 2015. The empirical results show that: (1) The per capita GDP growth among the three regions (namely, the eastern, central, and western regions of China) meets a conditional convergence trend, and the decreasing of the inter-region transportation costs increases the convergence speed; (2) The per capita GDP growth is in line with the club convergence trend within each of the three regions; (3) The trend of the output elasticity of the inter-region transportation costs shows that the gradual decrease of inter-region transportation costs has a positive correlation with the narrowing of economic disparity after the year 2000, accelerating "common prosperity" across different regions in China.     

Regional Exports and Economic Growth: The Case of Spanish Regions

Different variables have been considered growth enhancing. Traditionally, physical capital, human capital, and public capital have been considered. While the first two variables have been considered positive factors, the latter shows an ambiguous effect. The literature has also considered the role of exports in the economic growth process, introducing several arguments that test the hypothesis that exports are growth enhancing. One argument to be considered is that higher exports can increase total factor productivity due to returns to scale and that exports are an effective means to introduce advanced technology. To test this argument, an empirical analysis considered three possibilities, an export model, a demand model, and a mixed model that combined both. This empirical analysis was carried out for the various Spanish regions.     

中国地区经济增长与能源消费强度差异分析

本文假设我国西部与东部地区的能源消费强度差异是西部与东部地区人均GDP差异的函数,然后同其他回归变量一起检验这两个变量之间的关系,并通过使用面板数据计量经济学模型进行实证估计。本文的研究结论为:第一,总体而言,西部与东部地区的人均GDP差异存在收敛,随着人均GDP的收敛,西部与东部地区的能源消费强度差异也是收敛的,但收敛的速度慢于人均GDP的收敛速度。第二,不同西部省份在经济增长过程中的能源使用效率是收敛还是发散存在差异。本文的政策含义是:政府在制定区域经济发展战略时,要鼓励和引导各地区充分利用能源禀赋以及能源利用效率方面的差异进行合作,走能源节约型的可持续的区域平衡增长道路。     

地方政府竞争、投资冲动和我国宏观经济波动研究

利用国民收入核算公式,采用HP滤波分析方法,得到国民收入恒等式中各变量增长率的波动项,并依此构建了一个计量模型。然后利用各变量在1990-2004年间的分省数据,分析了各省GDP增长率波动的原因。结论表明,在我国的大多数省,投资增长率的波动是引起GDP增长率波动的主要因素。为剔除地域差异的影响,做了分区域的实证分析,其结果依然显示投资波动是各省GDP增长率波动的主要决定因素。进一步的分析表明,地方政府竞争是导致各省投资冲动、进而造成我国宏观经济波动的深层原因。     

Gender wage gap studies: consistency and decomposition

This paper reviews the empirical literature on the gender wage gap, with particular attention given to the identification of the key parameters in human capital wage regression models. This is of great importance in the literature for two main reasons. First, the main explanatory variables in the wage model, i.e., measures of work experience and time-out-of-work, are endogenous. As a result, applying traditional estimators may lead to inconsistent parameter estimates. Second, empirical evidence on the gender wage gap hinges on estimates of the parameters of interest. Accordingly, their economic meaning may be limited by restrictive assumptions included in wage models. This challenges both researchers and policymakers who require precise measures of the gender wage gap in order to create and enforce efficient equality policies. This paper is a substantially revised version of the first chapter of my thesis. I am grateful to Christian Dustmann and Wendy Carlin for their great support and comments. I also thank Bernd Fitzenberger, colleagues at the Norwegian School of Economics and Business Administration and IZA, and three anonymous referees for their helpful comments and suggestions.     

Time stability of the beta convergence among EU countries: Bayesian model averaging perspective

This paper analyzes the time stability of the GDP beta convergence in two subsamples: EU27 countries during 1993–2010 and EU15 during 1972–2010. Additionally, the article checks for the strength and stability of influence of particular economic growth factors. In order to address the problem of variables' selection, Bayesian model averaging (BMA) is used while choosing the appropriate variables for the regression. In order to loose the assumption of stability overtime in the regression, interaction terms of particular regressors are introduced with time dummies (the whole sample is divided into time intervals and is allowed for structural breaks). Finally, in order to address the problem of potential inconsistency of “typically used” estimators, the study employs Blundell and Bond's GMM system estimator. The main findings are the following. (1) The EU27 countries converged at the rate of about 5% per annum while the EU15 countries—at 3% p.a., which is an enormous difference as compared with the widely cited 2% rate of convergence. (2) The pure mechanism of conditional convergence of the countries under study was rather constant over time: there were periods of more rapid or slower convergence but the differences were not as huge as one could expect. (3) The considered economic growth determinants exhibited very mixed and differentiated impact on economic growth in various subperiods.     

人力资本投资效率的经济增长效应研究——基于四种面板数据回归模型的实证分析

本文借助中国30个省份1998～2008年的面板数据,以数据包络分析(DEA)得到的人力资本投资效率来指代各省的人力资本情况,综合采用普通面板回归、空间面板回归、门限面板回归以及平滑转换面板回归这四种回归模型进行分析后发现:人力资本投资效率在对经济增长有着显著贡献的同时,还存在明显的空间外溢效应和门限效应.基于这一结论,本文认为应当加大对邻省较多、经济发展水平较高且人力资本投资效率较低省份的科教支出并努力提升这些省份的人力资本投资效率;而对经济发展水平较低且人力资本投资效率较高的省份,不适宜从改进人力资本投资效率的思路来追求更快速的经济增长.     

Understanding the cell phone effect on vehicle fatalities: a Bayesian view

This article examines the potential effect of various factors on motor vehicle fatality rates using a rich set of panel data and classical regression analysis combined with Bayesian Extreme Bounds Analysis (EBA), Bayesian Model Averaging (BMA) and Stochastic Search Variable Selection (SSVS) procedures. The variables examined in the models include traditional motor vehicle and socioeconomic factors. In addition, the models address the effects of cell phone usage on such accidents. The use of both classical and Bayesian techniques diminish the model and parameter uncertainties which afflict more conventional modelling methods which rely on only one of the two methods.     

Endogeneity and panel data in growth regressions: A Bayesian model averaging approach

Bayesian model averaging (BMA) has been successfully applied in the empirical growth literature as a way to overcome the sensitivity of results to different model specifications. In this paper, we develop a BMA technique to analyze panel data models with fixed effects that differ in the set of instruments, exogeneity restrictions, or the set of explanatory variables in the regression. The large model space that typically arises can be effectively analyzed using a Markov Chain Monte Carlo algorithm. We apply our technique to investigate the effect of foreign aid on per capita GDP growth. We show that BMA is an effective tool for the analysis of panel data growth regressions in cases where the number of models is large and results are sensitive to model assumptions.