Availability Of Panel Data Research Articles

Influence of educational composition on firm innovation and performance

ABSTRACT Despite a strong focus on innovation from both politicians and managers, our current understanding of the relationship between managers’ education level and the educational composition of the workforce in terms of innovation and their joint association with performance remains limited. For example, while most studies include workforce quality as a control, and recognize its importance, there is still little knowledge about how it influences the innovation process. The data and estimation framework used in this study enable for a detailed analysis of the importance of both managers’ and workers’ skill intensity and workers’ skill diversity throughout the sequential innovation process that transforms ideas into valuable innovation in three stages. In addition, the availability of panel data allows us to account for various econometric issues, such as sample selection bias, reverse causality, simultaneity, and measurement errors. We conclude that educated managers, together with a balanced workforce across education length and field enhance both innovation and performance. Even more interestingly, we show that the educational level of managers influences the innovation process primarily through the recruitment of more educated workers with diverse educations. And the importance of including the indirect effect of educational composition through R&D decisions on the likelihood of innovation.

Impact of migration on household consumption expenditures in Bangladesh using the coarsened exact matching (CEM) approach

PurposeThe study aims to examine the impact of migration on household consumption expenditures in Bangladesh.Design/methodology/approachThe paper uses coarsened exact matching methods to examine the causal impact between migration and household welfare using the dataset on Bangladesh Household Income and Expenditure Survey 2010 on 12,213 households.FindingsThe study reveals that migration has a positive impact on household welfare improvement through increases in their consumption expenditures. Households with migration status are found to spend more on food, non-food (housing, durable goods, fuel, cosmetics, cleaning, transport, clothing, taxes, insurance, recreation) items and medical. However, the authors do not find any evidence of impacts on education expenditures.Research limitations/implicationsThe availability of panel data and the use of other variables (e.g. household investment expenditures, household budget allocation for agricultural input expenses, etc.) would have been able to provide vivid results.Originality/valueThis paper adds to the Bangladeshi migration literature by offering a novel empirical assessment of the Bangladeshi migrants and its impact on household welfare by drawing upon a recently published, nationally representative sample of Bangladeshi households.

Spatiotemporal analysis of Korean ginseng farm productivity

The past two decades has seen new methodological debates on the identification of production function. Olley and Pakes (J Polit Econ 101(6):1149–1164, 1996), Levinsohn and Petrin (Rev Econ Stud 70(2):317–340, 2003), and Ackerberg et al. (Econometrica 83(6):2411–2451, 2015) introduced nonparametric approaches to control for the unobserved productivity in the estimation of production function, which requires the availability of panel data. There has been an another body of the literature that argued that models that are typically estimated on the basis of panel data can also be identified with repeated cross-sections under certain conditions (Verbeek and Vella, 2005). The objective of this paper is two-fold. First, built on the insight of Verbeek and Vella (2005), this paper proposes a new approach to estimate the nonparametric control function based on repeated cross-sections. This is important because in many studies there is a lack of panel data where agents are followed over time, while repeated cross-sections may be available. Second, using cross-sections of Korean ginseng farms over 2006 to 2013, we apply our method to examine the evolution of farm-level productivity over time and across major production regions. Comparing our method with the pooled OLS regressions, the results show that the materials input coefficients are underestimated in the OLS regressions, which is consistent with the data where farms in the large ginseng production regions use relatively less materials than those in the other regions.

Using Choice Experiments to Find Double Jeopardy Patterns

Double jeopardy is one of the most important empirical patterns of consumer brand purchase behaviour. It asserts that large brands benefit from having more consumers who are also generally more loyal. Traditional methods for detecting double jeopardy patterns in consumer purchasing behaviour rely heavily on the availability of panel data. Although alternative methods have been proposed, these too require large quantities of data, making them costly to implement for many managers and researchers. This study proposes a new method for detecting double jeopardy patterns that requires only small samples of data. Using the instant coffee market in the US to test this new method, it is shown that repeated discrete choice experiments can produce proximate measures to those used as inputs to double jeopardy calculations. This approach gives researchers an economical and easy method to test whether a market conforms to double jeopardy, allowing them to keep managers informed about the properties of consumer purchase behaviour in their markets.

The effects of microfinance on child schooling: a retrospective approach

Two crucial problems when research agencies or donors need to assess empirically the microfinance/children education nexus on already operating organizations are lack of availability of panel data and selection bias. We propose an original approach which tackles these problems by combining retrospective panel data, fixed effects and comparison between pre- and post-treatment trends. The relative advantage of our approach vis-a-vis standard cross-sectional estimates (and even panels with just two time periods) is that it allows to analyse the progressive effects of microfinance on borrowers. With this respect, our article gives an answer to the widespread demand of impact methodologies required by regulators or by funding agencies which need to evaluate the current and past performance of existing institutions. We apply our approach to a sample of microfinance borrowers coming from two districts of Buenos Aires with different average income levels. By controlling for survivorship bias and heterogeneity in ...

Health dynamics, adaptation to illness and resource allocation

The increased availability of panel data has made it possible to estimate and measure health dynamics for population subgroups who may have systematically different levels of dynamics. We use a straightforward hypothetical example to investigate the implications of different levels of health dynamics on health outcomes, considering in addition the effects of adaptation to illness over time. The results demonstrate implications for the assessment of health technologies.

Sources of Productivity Growth in Health Services: A Case Study of Queensland Public Hospitals

Improving the performance of health sector is one of the most popular issues in Australia. This paper contributes to this important policy debate by examining the efficiency of health facilities in Queensland using the Malmquist Productivity Index (MPI). This method is selected because it is suitable for the multi-input, multi-output, and not-for-profit natures of public health services. In addition, with the availability of panel data we can decompose productivity growth into useful components, including technical efficiency changes, technological changes and scale changes. The results revealed an average of 1.6 per cent of growth in total factor productivity (TFP) among Queensland public hospitals in the study period. The main component contributing to the modest improvement of TFP during the period was catching-up at an average of 1.0 per cent. SFA estimates suggest that the number of nurses is the most influential determinant of output.

Voluntary Cooperation in the Commons? Evaluating the Sea State Program with Reduced Form and Structural Models

We utilize a variety of approaches to examine the success of a voluntary conservation program for a common property resource. The availability of panel data and a nonparticipatory group lets us use quasi-experimental methods to investigate the distribution of outcome treatment effects. We supplement these methods by incorporating a difference-in-differences structure into a behavioral model of fishing location choice to disentangle the program’s incentive effects from potentially misleading temporal variations in behavioral constraints. Our findings yield insight into the factors that support cooperation and illustrate the power of the complementary use of structural and reduced form models in program evaluation. <i>(JEL C21, Q22)</i>

Decomposition and Super-efficiency in the Korean Life Insurance Industry Employing DEA

The Korean life insurance industry has undergone profound changes, such as the beginning of the variable insurance in July 2001 and the bancassurance enforcement in August 2003. However, little empirical research has analyzed data that includes the bancassurance of life insurance companies operating in Korea. In response to this lack of research, this paper applies DEA (data envelopment analysis) models to measure and decompose their efficiency. We discovered that life insurance companies operating in Korea are a little different in their composition ratio of inputs and outputs, due to the increased variety of distribution channels and new products. We provided efficiency scores, return to scale, and reference frequencies. We also decomposed CCR, BCC, and SBM efficiency into scale efficiency and MIX efficiency. So, we try to investigate whether the sources of inefficiency were caused by the inefficient operation of DMU, disadvantageous conditions, the difference of the composition ratio in inputs and outputs with reference sets, or any combination of the above. Most companies in the sample display had either constant or decreasing returns to scale. The efficiency rankings were less consistent among models and efficient DMUs. In response to this problem, we used the super-efficiency model to rank them and then compared the rankings of the DMUs among the various models. It was also concluded that the availability of panel data, rather than cross-sectional data, would greatly improve the validity of the efficiency estimates.

Comments on: Panel data analysis—advantages and challenges

This paper provides an excellent review of panel data methods and their application in economics. Professor Hsiao is the leading authority on panel data econometrics; he wrote the first textbook on the subject that appeared as an econometric society monograph in 1986 with the second edition appearing in 2003. As the author points out in the introduction, it is impossible to do justice to the vast and growing literature on panel data. In my discussion, I will try to complement his review with additional references that the reader might want to read. These papers are discussed in the panel data textbooks cited in the paper including Hsiao (2003), Arellano (2003) and Baltagi (2005). The paper starts by reviewing the advantages of panel data arguing that the proliferation of panel applications in economics is due to the wider availability of panel data in both developed and developing countries. Because of space limitations, the paper does not go into pseudo-panels. These are panels constructed from consumer surveys which may not involve the same individuals or households. It does so, by focusing on cohorts, see Deaton (1985). Also, the paper does not have the space to discuss problems of attrition in panels which can be somewhat alleviated with refreshment samples, or rotating panels, see Biorn (1981). Advantages of panel data over time series data or cross-section data is more degrees of freedom, less multicollinearity, and more variation in the data that results in

The Application of Mathematical Programming Approaches to Estimating Container Port Production Efficiency

Container terminal production is both an important and complicated element in the contemporary global economy. This paper aims to evaluate the efficiency of the world’s most important container ports and terminals using the two alternative techniques of Data Envelopment Analysis (DEA) and the Free Disposal Hull (FDH) model. The results give an insight into the current efficiency ranking of the world’s major container ports and terminals. They also confirm expectations that the available mathematical programming methodologies lead to different results and that appropriate variable definition of input and output factors is a crucial element in meaningful applications of DEA and FDH. It is also concluded that the availability of panel data, rather than cross-sectional data would greatly improve the validity of the efficiency estimates derived from all the mathematical programming techniques applied.

Maintenance of and Innovation in Long-term Panel Studies: The Case of the German Socio-Economic Panel (GSOEP)

The availability of panel data on the basis of micro data has become an indispensable component of the infrastructure of empirically oriented social scientists and economists. This is also a consequence of the fact that, for a panel survey, the quality of both content and methodological analyses increases with each new wave. Especially the number of events which can be analyzed increases (e.g., social and regional mobility, life-course transitions like changing employment, occupational careers, family events and even death). In the USA, the Study of Income Dynamics (PSID) has been running since 1968. In principle it was the prototype for the German Socio-Economic Panel Study (SOEP), which was started in 1984. However, the SOEP has its own features, e.g. the surveying of all adult household members, which made the SOEP itself a role model for all of the other panel studies which followed over the course of time. Survey data comparable to the SOEP which are easily assessable for researchers exist, for example, in Great Britain, the Netherlands, Russia, Hungary, Switzerland, and since 2001 in Australia.

Lohnbedingter Mismatch auf deutschen Arbeitsmärkten? Lehren aus einem Vergleich mit Portugal / Wage-Induced Mismatch on German Labour Markets? Lessons from Comparison with Portugal

Zusammenfassung Die Analyse von Paneldaten für Deutschland und Portugal und die Schätzung von Matching- Funktionen für Berufsgruppen zeigt in Deutschland eine fallende und in Portugal eine steigende Effizienz des Matching-Prozesses. Löhne in Deutschland und Mindestlöhne in Portugal sind signifikante Faktoren für die jeweilige Entwicklung. Berechnungen ergeben, daß in (West-) Deutschland im Zeitraum 1971 bis 1995 eine Halbierung der Reallohnzuwächse zu einer Steigerung der Effizienz des Matching-Prozesses um ca. 40 % geführt hätte. Ferner stellt sich heraus, daß eine Beschleunigung der beruflichen Mobilität vom Produzierenden Gewerbe in Richtung Dienstleistungsbereich die Effizienz des Matchings erhöhen würde.

Assessing poverty: some reflections on the literature.

"This paper examines the quantitative poverty measurement literature. After describing the literature a number of issues in poverty research are discussed. It can be concluded that the framework for poverty assessments is not always fixed. Much has been written about the poverty line but the issue of updating it seems to have attracted less attention than deserved. Substantial advancements in poverty research have been gained by fuller reports on the extent of poverty through the use of poverty indices and because of increased availability of panel data."

Women and Minorities in Federal Government Agencies: Examining New Evidence from Panel Data

The employment of women and racial/ethnic minorities in the public work force has grown considerably in the past 20 years, and projections have suggested that such growth can be expected to continue into the immediate future (Johnston et al., 1988). Already, die federal civil service has, in the aggregate, become remarkably reflective of the nation's population. Women comprise more than 43 percent of the total federal civilian work force while African Americans hold 16.6 percent of those positions, and Hispanic representation stands at 5.4 percent (U.S. Office of Personnel Management, 1990a). This level of integration has, however, failed to reach all segments of the public bureaucracy. Women and minorities remain concentrated in lower-echelon jobs. Much attention has focused recently on that issue and on ways to ensure that equal opportunity reaches the higher grades in the public service;(1) yet, there is considerable variation across federal agencies in the overall percentage of jobs held by women and minorities and the rate of growth of minority and female employment. These differences are illustrated in Tables 1 and 2, which report employment shares for women, African Americans, and Hispanics in 30 selected agencies for the year 1988, and the percentage increase in employment shares for each group from 1982-1988, respectively. (The term is used to refer to departments as well as independent agencies.) [TABULAR DATA OMITTED] The empirical issue addressed in this article is the extent to which interagency differences in female and minority employment shares, as well as share changes, are systematically related to the distribution of occupations within an agency and an agency's demographic and organizational characteristics. A distinctive feature of this analysis is the use of panel data, a pooled cross-section/time-series see grey box on page 266.) Previous empirical work has relied amost exclusively on crosssectional econometric approaches. The availability of panel data allows for control of the passage of time and of unobserved time-invariant agency characteristics that may be correlated with explanatory variables in subsequent regressions. Such control is not possible in standard cross-sectional analysis, and as a result, coefficient estimates from such models may be inconsistent. Agency Characteristics and the Employment of Women and Minorities In any study of determinants of government employment integration along gender, racial, and ethnic lines, attention should be directed to the distribution of occupations across agencies. Traditionally, women and minorities have been over-represented in clerical positions and under-represented in professional, administrative, and technical job categories (Saltzstein, 1986; Mladenka, 1989; Kellough, 1990; and Kellough and Elliott, 1992). As a result, it can be expected that the estimated effect of the percentage of clerical positions on the employment of women and minorities will be positive. Similarly, because of the over-representation of African-American and Hispanic employees in blue-collar positions, the prevalence of blue-collar positions in an agency should be positively associated with African-American and Hispanic employment. By contrast, female and minority employment should vary inversely with the percentage of professional, administrative, and technical occupations in an agency. Apart from occupational variation, however, federal agencies also differ dramatically in terms of their size or total employment. Grabosky and Rosenbloom (1975) provided early evidence that minority employment shares are negatively related to agency size. One explanation for this relationship is that each additional minority (or female) hire makes a smaller contribution toward diversity in large agencies; such agencies must employ a larger number of minorities to achieve the same racial/ethnic composition as smaller agencies. …

Panel data analysis: An introductory overview

Our ability to manipulate large datasets rapidly on personal computers, together with the increasing availability of panel data on individuals and firms, has revolutionized empirical microeconomics. It should also revolutionize our understanding of the microeconomy and allow us to evaluate received wisdom gained from aggregate time series and micro cross-section data alike. The list of important new applied papers using panel data is too long to mention and so we provide a brief overview of panel data analysis, noting some of the advantages while warning of some potential pitfalls. Panel data refers to cross-section data that have been pooled over time where the same individual agents are followed through time. A common feature of such datasets is that, whereas the number of agents ‘N’ (firms or households) is large, the number of time periods ‘T’ is relatively short. For example, we may have in excess of 400 firms in each company cross-section but only 10 or fewer annual observations on each. A number of attractive features of such data immediately suggest themselves. Time series or temporal analysis can be explored without suffering aggregation bias common in ‘macroeconometric’ studies. Moreover, the consistency of the estimated parameters can often be proved for fixed T provided the cross-section dimension is ‘large’. Indeed, the aim of many microeconometric studies has been to estimate dynamic or temporal effects from relatively few time-series observations exploiting large N asymptotics. However, this result relies fairly heavily on the idiosyncratic nature of micro error terms and considerable care is needed in assessing the appropriateness of large N asymptotics on short panels. Nevertheless, it is clear that features common to individuals across time but which differ across them in any time period can be relatively easily eliminated, removing much of the importance of modelling permanent individual specific unobservable effects which makes analysis on single cross-sections so difficult. This is particularly true where individual specific unobservables are correlated with included regressors. Most importantly perhaps, panel data allow the analyst to exploit the large variation in circumstance of different individuals in any cross-section while still recovering temporal effects in behaviour. As a panel data illustration we can imagine investigating the relationship between taxation and investment behaviour. Clearly

Estimation of a fixed-effect Cobb–Douglas system using panel data

This paper considers the estimation of a model consisting of a Cobb–Douglas production function and the associated first-order conditions for cost minimization. There is a fixed individual (firm) effect in each equation, and the availability of panel data is assumed. The conditional MLE is derived and shown to be MLE after a within transformation. It can be written explicitly as a corrected OLS estimator or as an IV estimator. In the special case in which the errors in the production function are independent of the errors in the first-order conditions, the conditional MLE does not require input price data.