Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

Statsmodels is a library for statistical and econometric analysis in Python. This paper discusses the current relationship between statistics and Python and open source more generally, outlining how the statsmodels package fills a gap in this relationship. An overview of statsmodels is provided, including a discussion of the overarching design and philosophy, what can be found in the package, and some usage examples. The paper concludes with a look at what the future holds.

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Statsmodels: Econometric and Statistical Modeling with Python

This paper surveys the most important developments in multivariate ARCH-type modelling. It reviews the model specifications, the inference methods, and the main areas of application of these models in financial econometrics.

Multivariate GARCH Models: A Survey

This paper surveys the most important developments in multivariate ARCH-type modelling. It reviews the model specifications and inference methods, and identifies likely directions of future research.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jae.842

Multivariate GARCH models: a survey

This paper examines to what extent recent empirical evidence can collectively and systematically substantiate the claim that entrepreneurship has important economic value. Hence, a systematic review is provided that answers the question: What is the contribution of entrepreneurs to the economy in comparison to non-entrepreneurs? We study the relative contribution of entrepreneurs to the economy based on four measures that have most widely been studied empirically. Hence, we answer the question: What is the contribution of entrepreneurs to (i) employment generation and dynamics, (ii) innovation, and (iii) productivity and growth, relative to the contributions of the entrepreneurs' counterparts, i.e. the 'control group'? A fourth type of contribution studied is the role of entrepreneurship in increasing individuals' utility levels. Based on 57 recent studies of high quality that contain 87 relevant separate analyses, we conclude that entrepreneurs have a very important - but specific - function in the economy. They engender relatively much employment creation, productivity growth and produce and commercialize high quality innovations. They are more satisfied than employees. More importantly, recent studies show that entrepreneurial firms produce important spillovers that affect regional employment growth rates of all companies in the region in the long run. However, the counterparts cannot be missed either as they account for a relatively high value of GDP, a less volatile and more secure labor market, higher paid jobs and a greater number of innovations and they have a more active role in the adoption of innovations.

What is the Value of Entrepreneurship? A Review of Recent Research

In this paper, we carry out an econometric analysis on the adoption and effective use of Information and Communication Technologies (ICTs) among a sample of Italian SMEs. An important result is that, in order to understand the main factors that drive SMEs to the adoption of ICTs, it is useful to divide the available technologies according to a taxonomy based on their typical function. Along with general-use ICTs (e-mail and Internet access), we identify two groups of technologies (labelled production-integrating and market-oriented ICTs) the use of which is associated with different firm characteristics. In both cases, however, the availability of highly educated workers turns out to be a key factor. Policy implications are also discussed.

The Adoption of ICT among SMEs: Evidence from an Italian Survey

Endogeneity and sample selection in a model for remittances

This paper offers a methodological contribution to the empirical analysis of the relationship between banking and economic growth by suggesting a new indicator for the state of development of the banking system based on a measure of bank microeconomic efficiency. This choice helps to overcome the problem of causality and to capture the effects of banks’ activity on growth. This new approach is then applied to analyse the relationship between the banking system and economic growth in the Italian regions, through a dynamic panel technique. The empirical results show the existence of an independent effect exerted by the efficiency of banks on regional growth.

/pdf/banks-inefficiency-and-economic-growth-a-micro-macro-1fd8pu2vfp.pdf

Banks’ Inefficiency and Economic Growth: A Micro‐Macro Approach

Financial development and remittances: Micro-econometric evidence

Multivariate GARCH models constitute the workhorse of empirical applications in several fields, a notable example being financial econometrics. Unfortunately, ML (or quasi-ML) estimation of such models, although relatively straightforward in theory, is often made difficult by the fact that available software relies on numerical methods for computing the first derivatives of the log-likelihood; the fact that these models often include a large number of parameters makes it impractical to estimate even medium-sized models. In this paper, closed-form expressions for the score of the BEKK model of Engle and Kroner (1995) are obtained, and strategies for efficient computation are discussed.

Riccardo Lucchetti

Papers

The Adoption of ICT among SMEs: Evidence from an Italian Survey

Endogeneity and sample selection in a model for remittances

Banks’ Inefficiency and Economic Growth: A Micro‐Macro Approach

Financial development and remittances: Micro-econometric evidence

Analytical Score for Multivariate GARCH Models