Renewable energy innovations in Europe: a dynamic panel data approach

We investigate the determinants of renewable energy R&D intensity and the impact of renewable energy innovations on firm performance, using several dynamic panel data models. We estimate these models using a large data set of European firms from 19 different countries, with some patenting activity in areas related to renewable energies during the 1987 to 2007 period. Our results confirm our priors on the determinants of the rapid development of renewable energy R&D intensity during the past decades. Additionally, we find evidence that renewable patent intensity has a significant dynamic impact on the stock market value of firms.     

Locally adjusted LM test for spatial dependence in fixed effects panel data models

Lee and Yu (2010) propose spatial panel data models with one-way and two-way fixed effects. Debarsy and Ertur (2010) construct LM (Lagrange multiplier) and LR (likelihood ratio) tests in the one-way fixed effects model. He and Lin (2012) derive LM tests in the two-way fixed effects model. To guard against possible local misspecification, in this paper we apply Bera and Yoon (1993) principle, and construct locally adjusted (robust) LM tests for spatial dependence in both one-way and two-way fixed effects models. Monte Carlo experiment is carried out to show the advantage of using robust LM tests over the corresponding marginal and conditional versions.     

Factors affecting trade in services: evidence from panel data

In the course of economic development, nations have typically progressed through stages in which agriculture, then manufacturing and, finally, services predominate. Concerns around the sustainability of manufacturing and goods export-led growth raise the importance of trade in services. In the context of a panel model, controlling for the factors that determine trade in general, we examine the determinants of trade in services in a sample of 46 countries over the decade 2004–2015. We find an ambiguous pattern of effects from institutional quality but strong evidence of the importance of trade in goods for trade in services.     

Geopolitical risks and recessions in a panel of advanced economies: evidence from over a century of data

This paper uses a panel of 17 advanced countries over the annual period of 1899–2013, to analyze for the first time, the role played by geopolitical risks in predicting recessions. After controlling for other standard predictors based on a logit model, we find that while aggregate geopolitical risks do not have any predictive ability, geopolitical acts enhance the probability of future recessions, with geopolitical threats reducing the same.     

The returns to general experience,job and occupational tenure: a study using Australian panel data

This article uses Australian panel data for the years 2001–2009 to estimate returns to general experience, job and occupational tenure. We pay particular attention to issues of unobserved heterogeneity bias in our estimations. We find that both general experience and occupational tenure have statistically and numerically significant effects on wage outcomes, even after controlling for unobserved heterogeneity. Job tenure on the other hand only seems to matter in OLS regressions that do not control for heterogeneity biases. Once these biases are controlled for, only a modest effect from job tenure remains. The inclusion of occupational tenure in the estimating equation tends to negate even this modest job tenure effect. The only exception to this is for workers in large organizations. For these workers a small but statistically significant effect from job tenure remains, even once we have controlled for heterogeneity and included occupational tenure in the estimating equation. The results reported in this article have implications for the various theories of the labour market that predict upward-sloping wage-job-tenure profiles.     

The driving forces of the change in China's energy intensity: An empirical research using DEA-Malmquist and spatial panel estimations

Energy shortage and environmental degradation have become significant hurdles for China's sustainable development nowadays. One of the most efficient and effective ways to ease energy shortage is to sufficiently reduce energy intensity. In the extant literature on the influential factors of China's energy intensity, the regional imbalance and spatial spillover effects were basically ignored, which may yield to biased and unreasonable results. As a result, in this paper, the driving forces of China's provincial energy intensity were for the first time investigated by combining the Data Envelopment Analysis (DEA)-Malmquist and spatial panel approaches for the period between 2000 and 2014. The results indicate that technological progress plays a dominant role in decreasing China's overall energy intensity. In both the Eastern and Central regions, the technological progress and its components can decrease energy intensity, while this effect doesnot significantly exist in the Western region. Rapid industrialization should be responsible for China's currently high energy intensity, while energy price hiking is conducive to the decrease in energy intensity. Moreover, there is also clear evidence that these factors influence on energy intensity partly through the spatial spillover effects.     

Simulation-based inference in dynamic panel probit models: An application to health

This paper considers the determinants of a binary indicator for the existence of functional limitations using seven waves (1991–1997) of the British Household Panel Survey (BHPS). The focal point of our analysis is the contributions of state dependence, heterogeneity and serial correlation in explaining the dynamics of health. To investigate these issues we apply static and dynamic panel probit models with flexible error structures. To estimate the models we use maximum simulated likelihood (MSL) with antithetic acceleration and implement a recently proposed test for the existence of asymptotic bias. The dynamic models show strong positive state dependence. Data from the British Household Panel Survey (BHPS) were supplied by the ESRC Data Archive. Neither the original collectors of the data nor the Archive bear any responsibility for the analysis or interpretations presented here. Funding was provided by the ESRC award no: R000238169-Simulation-based econometric approaches to investigating the interaction of lifestyle and health. The authors would like to thank William Greene for valuable comments on an earlier draft of the paper, Roberto Leon Gonzalez for valuable programming advice, and participants at the iHEA Third International conference, York, 22–25 July 2001 and York Seminars in Health Econometrics (YSHE) for their comments.     

Augmenting travel cost models with contingent behavior data

This paper proposes contingent behavior survey questions as a valuable supplement to observed data in travel cost models of non-market demand for recreational resources. A set of observed and contingent behavior results for each survey respondent allows the researcher to control for individual heterogeneity by taking advantage of panel data methods when exploring the nature of respondent demands. The contingent scenarios also provide opportunities to (a) test for differences between observed and contingent preferences and/or (b) assess likely demands under conditionsbeyond the domain of observed variation in costs or resource attributes. Most importantly, contingent scenarios allow the researcher to imposeexogenously varying travel costs. Exogenous imposition of travel costs together with panel methods reduces the omitted variables bias that plagues observed-data travel cost models of recreational demand. Using a convenience sample of data for illustrative purposes, we show how to estimate the demand for recreational angling by combining observed and contingent behavior data. We begin with simple naive pooled Poisson models and progress to more theoretically appropriate fixed effects panel Poisson specifications.The authors are at the University of Nevada and UCLA, respectively. We gratefully acknowledge the comments of both Scott Shonkwiler and participants in the W133 meetings in Santa Fe, New Mexico and for research material provided by Wayne Gray. The data were provided by Rang Narayanan. Research assistance was provided by Jerry McGraw and Natalie Tucker. Research partially supported by the Nevada Experiment Station. Any errors or omissions remain the authors' responsibility.     

A count data model with endogenous household specific censoring: the number of nights to stay

In this paper a count data regression model accounting for endogenous censoring with household specific censoring thresholds is presented. The presented modelling approach is utilized in an analysis of household choice of total number of nights to spend on monthly recreational trips. The empirical study reveals that the suggested approach is feasible and that accounting for endogenous censoring gives a better fit to the data. For helpful comments on an earlier version of the paper we thank two anonymous referees.     

The Labour Input Response to Permanent Changes in Output: An Errors-in-Variables Analysis Based on Panel Data

Using panel data for Norwegian manufacturing, we revisit 'the increasing returns to scale puzzle' for labour inputs. We consider the response of the input of white-collar workers, blue-collar workers, and blue-collar worker hours to permanent changes in output. Permanent and temporary changes in output are treated as latent variables. We compare OLS, IV, and GMM estimates of the response elasticities and conclude that the distinction between permanent and temporary changes is essential. Our GMM estimates suggest that the 'increasing returns to scale puzzle' remains for all measures of the labour input also when we consider their response to permanent changes in output. For materials, the output response indicates approximately constant returns to scale. This suggests non-homotheticity of the production technology.
JEL classification : C 23; J 23     

Impact of Bt cotton on pesticide poisoning in smallholder agriculture: A panel data analysis

While substantial research on the productivity and profit effects of Bt cotton has been carried out recently, the economic evaluation of positive and negative externalities has received much less attention. Here, we focus on farmer health impacts resulting from Bt-related changes in chemical pesticide use. Previous studies have documented that Bt cotton has reduced the problem of pesticide poisoning in developing countries, but they have failed to account for unobserved heterogeneity between technology adopters and non-adopters. We use unique panel survey data from India to estimate unbiased effects and their developments over time. Bt cotton has reduced pesticide applications by 50%, with the largest reductions of 70% occurring in the most toxic types of chemicals. Results of fixed-effects Poisson models confirm that Bt has notably reduced the incidence of acute pesticide poisoning among cotton growers. These effects have become more pronounced with increasing technology adoption rates. Bt cotton now helps to avoid several million cases of pesticide poisoning in India every year, which also entails sizeable health cost savings.     

Modeling quality demand with data from Household Budget Surveys: An application to meat and fish products in Greece

In this paper, we employ a method to examine the factors affecting quality choice by Greek households, using cross-sectional survey data. We illustrate the method using the raw data of the 2004/05 Household Budget Survey for meat and fish products. Quality elasticities of total food expenditure and household's age structure are derived. To cope with the zero expenditure problem, Heckman's two-step method is employed. Results generally suggest that several socio-economic factors affect quality demand for meat and fish.     

A panel data approach to the demand for money and the effects of financial reforms in the Asian countries

Alternative panel data estimation methods are used to estimate the cointegrating equations for the demand for money (M1) for a panel of 14 Asian countries from 1970 to 2005. The effects of financial reforms are analyzed with estimates for two sets of sub-samples and two break dates. Our results show that money demand function has been stable and financial reforms are yet to have any significant effects. Since there is no evidence for instability in the demand for money, the central banks of these countries should use money supply, instead of the rate of interest, as the monetary policy instrument.     

中国装备制造业的出口依存度及对外市场的需求弹性研究——基于行业面板数据的分析

文章利用装备制造业7个子行业2001-2009年出口交货值和产业销售值数据,对产业的对外市场需求弹性进行了动态实证研究,并在此基础上利用7个子行业的对外市场需求弹性系数作为权重,对装备制造业的对外依存度进行了新的计算。研究结果表明,装备制造业7个子行业在短期内对外市场需求缺乏弹性,而部分行业在长期内对外市场需求富有弹性;根据对外依存度的传统定义,在产业迅速发展时期,由于没有考虑到市场需求弹性因素,对产业的对外依存度存在高估。     

Testing for the presence of some features of increasing returns to adoption factors in energy system dynamics: An analysis via the learning curve approach

The purpose of this paper is to explain the sources of energy system lock-in. It presents a comparative analysis of the respective contributions of some features of increasing returns to adoption factors, i.e. learning-by-doing, learning-by-searching and returns to scale effects in explaining the technological change dynamics in the energy system. The paper is technically based on a critical analysis of the learning curve approach. Econometric estimation of learning and scale effects inherent to seven energy technologies were performed by the use of several learning curve specifications. These specifications permit to deal with some crucial issues related to the learning curve estimation which are associated with the problem of omitted variable bias, the endogeneity effects and the choice of learning indicators. Results show that dynamic economies from learning effects coupled with static economies from scale effects are responsible for the lock-in phenomena of the energy system. They also show that the magnitude of such effects is correlated with the technology life cycle (maturity). In particular, results point out that, 1) the emerging technologies exhibit low learning rates associated with diseconomies of scale which are argued to be symptomatic of the outset of the deployment of new technologies characterized by diffusion barriers and high level of uncertainty, 2) the evolving technologies present rather high learning rates meaning that they respond quickly to capacity expansion and R&D activities development, 3) conventional mature technologies display low learning rates but increasing returns to scale implying that they are characterized by a limited additional diffusion prospects.     

Goodness-of-fit techniques for count data models: an application to the demand for dental care in Spain

This paper compares the practical performance of alternative goodness-of-fit techniques for count data models in the context of a study of the determinants of demand for dental care in Spain. We apply alternative goodness-of-fit techniques to different specifications. In particular, we implement recently proposed specification tests which are consistent in the direction of general nonparametric alternatives. The analysis suggests that a negative binomial model is an appropriate specification for dental care demand. Dental health and income are identified as important predictors of individuals' behavior. First version received: April 2000/Final version received: March 2001     

国外专利申请对技术进步的影响——基于中国各地区面板数据的分析

笔者通过借鉴Coe ＆ Helpman的贸易溢出模型，构建国外专刊申请的技术溢出模型，并运用Litchtenberg和Pottelsbengh提出的国外研发存量的度量方法，对国外专刊申请包含的研发存量进行量化，并在此基础上就国外专利申请对中国技术进步的影响进行实证分析。结果表明：国外专利申请对中国技术进步具有促进作用，但对东、中、西部技术进步的贡献度存在差异。     

房地产投资在地方经济发展中的影响研究——基于东部10个省市的经验分析

在构建房地产投资与地方经济增长的面板数据模型基础上,利用东部地区10个省市1996～2009年的数据,就房地产投资对地方经济增长的影响进行了实证检验。结果显示,房地产投资通过其投资效应和极强的产业波及效应推动了东部地区各省市的经济增长,但是这种增长效应并不显著,弱于同期的人力资本形成、物质资本投资和外贸发展的推动效应。     

Demand system estimation in the absence of price data: an application of Stone-Lewbel price indices

This article evaluates the feasibility of estimating a system of demand equations in the absence of price information using the approach developed by Lewbel (1989). Stone-Lewbel (SL) price indices for commodity groups are constructed using information on the budget shares and the Consumer Price Indices (CPIs) of the goods comprising the commodity groups, which allows for household-level prices to be recovered. This study evaluates how susceptible are elasticities and marginal effects estimates from traditional parametric demand systems to the CPI used in the construction of the SL prices. To do this, three alternative regional CPIs are considered for the construction of the SL prices: monthly, quarterly and a constant (unity) price index. Elasticities and marginal effect estimates are computed for eight food commodity groups using the Exact Affine Stone Index (EASI) model as the parametric demand system and data from the United States Consumer Expenditure Survey. The estimates proved to be robust to the alternative regional CPIs considered in the construction of SL price indices, even to the absence of one. Hence, the results suggest that it is possible to accurately estimate a demand system even in the absence of price information.     

Long- and short-run elasticities of residential electricity consumption in China: a partial adjustment model with panel data

While it has stabilized in developed world, the per capita residential electricity consumption (REC) in developing countries such as China is growing very rapidly and this trend is very likely to continue. Built upon a provincial level panel data, we employ a partial adjustment model to investigate the future trend of REC in China and factors that affect it. We estimate the income and price short-term and long-term elasticities for urban and rural China, respectively and compare the results with REC studies in other countries or regions. The findings provide useful information to understand how the REC would grow in China as household income increases and how effective that price could be as an intervention tool.