Corruption and Education: Empirical evidence from cross-country micro-data

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Inequality over the business cycle: Estimating income risk using micro-data on consumption

We use CEX repeated cross-section data on consumption and income, to evaluate the nature of increased income inequality in the 1980s and 90s. We decompose unexpected changes in family income into transitory and permanent, and idiosyncratic and aggregate components, and estimate the contribution of each component to total inequality. The model we use is a linearized incomplete markets model, enriched to incorporate risk-sharing while maintaining tractability. Our estimates suggest that taking risk sharing into account is important for the model fit; that the increase in inequality in the 1980s was mainly permanent; and that inequality is driven almost entirely by idiosyncratic income risk. In addition we find no evidence for cyclical behavior of consumption risk, casting doubt on Constantinides and Duffie s (1995) explanation for the equity premium puzzle.

The regional distribution of unemployment. What do micro-data tell us?

Regional disparities in unemployment rates are large and persistent. The literature provides evidence of their magnitude and evolution, as well as evidence of the role of certain economic, demographic and environmental factors in explaining the gap between regions of low and high unemployment. Most of these studies, however, adopt an aggregate approach and so do not account for the individual characteristics of the unemployed and employed in each region. This paper, by drawing on micro-data from the Spanish wave of the Labour Force Survey, seeks to remedy this shortcoming by analysing regional differentials in unemployment rates. An appropriate decomposition of the regional gap in the average probability of being unemployed enables us to distinguish between the contribution of differences in the regional distribution of individual characteristics from that attributable to a different impact of these characteristics on the probability of unemployment. Our results suggest that the well-documented disparities in regional unemployment are not just the result of regional heterogeneity in the distribution of individual characteristics. Non-negligible differences in the probability of unemployment remain after controlling for this type of heterogeneity, as a result of differences across regions in the impact of the observed characteristics. Among the factors considered in our analysis, regional differences in the endowment and impact of an individual’s education are shown to play a major role.

Micro Data Repositories: Increasing the Value of Research on the Web

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

How does employment density influence individuals’ wages? : A micro data approach.

We estimate the effect of employment density on wages in Sweden in a large geocoded data set on individuals and workplaces. Employment density is measured in four circular zones around each individual’s place of living. The data contains a rich set of control variables that we use in an instrumental variables framework. Results show a relatively strong but rather local positive effect of employment density on wages. Beyond 5 kilometers the effect becomes negative. This might indicate that the effect of agglomeration economies falls faster with distance than the effects of congestion.

Technology, trade and skills in Brazil: evidence from micro data

Includes bibliography

Restoration of micro data of John Lossing Buck's survey and analysis of the inverse relationship between yield and farm size in rural China in the 1930's

A large scale Chinese agricultural survey was conducted at the direction of John Lossing Buck from 1929 through 1933. At the end of the 1990’s, some parts of the original micro data of Buck’s survey were discovered at Nanjing Agricultural University. An international joint study was begun to restore micro data of Buck’s survey and construct parts of the micro database on both the crop yield survey and special expenditure survey. This paper includes a summary of the characteristics of farmlands and cropping patterns in crop yield micro data that covered 2,102 farmers in 20 counties of 9 provinces. In order to test the classical hypothesis of whether or not an inverse relationship between land productivity and cultivated area may be observed in developing countries, a Box-Cox transformation test was conducted for functional forms on five main crops of Buck’s crop yield survey. The result of the test shows that the relationship between land productivity and cultivated areas of wheat and barley is linear and somewhat negative; those of rice, rapeseed, and seed cotton appear to be slightly positive. It can be tentatively concluded that the relationship between cultivated area and land productivity are not the same among crops, and the difference of labor intensity and the level of commercialization of each crop may be strongly related to the existence or non-existence of inverse relationships.

Identifying Factor Productivity from Micro-data: The case of EU agriculture. Factor Markets Working Paper No. 34, January 2013

The classical problem of agricultural productivity measurement has regained interest owing to recent price hikes in world food markets. At the same time, there is a new methodological debate on the appropriate identification strategies for addressing endogeneity and collinearity problems in production function estimation. We examine the plausibility of four established and innovative identification strategies for the case of agriculture and test a set of related estimators using farm-level panel datasets from seven EU countries. The newly suggested control function and dynamic panel approaches provide attractive conceptual improvements over the received ‘within’ and duality models. Even so, empirical implementation of the conceptual sophistications built into these estimators does not always live up to expectations. This is particularly true for the dynamic panel estimator, which mostly failed to identify reasonable elasticities for the (quasi-) fixed factors. Less demanding proxy approaches represent an interesting alternative for agricultural applications. In our EU sample, we find very low shadow prices for labour, land and fixed capital across countries. The production elasticity of materials is high, so improving the availability of working capital is the most promising way to increase agricultural productivity.

The Reallocation of Agricultural Labour across Sectors: An Empirical Strategy for Micro Data. Factor Markets Working Document No. 45, May 2013

This paper presents an empirical methodology for studying the reallocation of agricultural labour across sectors from micro data. Whereas different approaches have been employed in the literature to better understand the mobility of labour, looking at the determinants to exit farm employment and enter off-farm activities, the initial decision of individuals to work in agriculture, as opposed to other sectors, has often been neglected. The proposed methodology controls for the selectivity bias, which may arise in the presence of a non-random sample of the population, in this context those in agricultural employment, which would lead to biased and inconsistent estimates. A 3-step multivariate probit with two selection and one outcome equations constitutes the selected empirical approach to explore the determinants of farm labour to exit agriculture and switch occupational sector. The model can be used to take into account the different market and production structures across European member states on the allocation of agricultural labour and its adjustments.

Searching for structure (alias-AID-III) ; an approach to analysis of substantial bodies of micro-data and documentation for a computer program (successor to the Automatic Interaction Detector Program) /

Bibliography: p. [165]-166.

Searching for structure ; an approach to analysis of substantial bodies of micro-data and documentation for a computer program /

Mode of access: Internet.

The Long-Term impact of Business Support? - Exploring the Role of Evaluation Timing using Micro Data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

The long-term impact of business support? - Exploring the role of evaluation timing using micro data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

Combining micro and macro data in hedonic price indexes

This paper proposes arithmetic and geometric Paasche quality-adjusted price indexes that combine micro data from the base period with macro data on the averages of asset prices and characteristics at the index period.

The role of big data in governance: a regulatory and legal perspective of analytics in global financial services

This paper discusses how global financial institutions are using big data analytics within their compliance operations. A lot of previous research has focused on the strategic implications of big data, but not much research has considered how such tools are entwined with regulatory breaches and investigations in financial services. Our work covers two in-depth qualitative case studies, each addressing a distinct type of analytics. The first case focuses on analytics which manage everyday compliance breaches and so are expected by managers. The second case focuses on analytics which facilitate investigation and litigation where serious unexpected breaches may have occurred. In doing so, the study focuses on the micro/data to understand how these tools are influencing operational risks and practices. The paper draws from two bodies of literature, the social studies of information systems and finance to guide our analysis and practitioner recommendations. The cases illustrate how technologies are implicated in multijurisdictional challenges and regulatory conflicts at each end of the operational risk spectrum. We find that compliance analytics are both shaping and reporting regulatory matters yet often firms may have difficulties in recruiting individuals with relevant but diverse skill sets. The cases also underscore the increasing need for financial organizations to adopt robust information governance policies and processes to ease future remediation efforts.