Entrepreneurship and survival dynamics of immigrants to the U.S. and their descendants

Many studies have explored the determinants of entering into entrepreneurship and the differences in self-employment rates across racial and ethnic groups. However, very little is known about the survival in entrepreneurship of immigrants to the U.S. and their descendants.We adopt a modeling framework based on duration analysis, which takes into account both the fact that the stock of entrepreneurs initially observed represents a selected sample and the inability of observing in the data the exit time for some spells. Unlike previous studies, we find a lower survival probability in entrepreneurship for Mexican and other Hispanic immigrants, which does not carry on to their U.S.-born descendants. We also find that these two immigrant groups tend to enter entrepreneurship from unemployment or inactivity and they are more likely to exit towards employment in the wage sector, suggesting that entrepreneurship represents for them an intermediate step from non-employment to paid employment.     

Estimating demand with distance functions: Parameterization in the primal and dual

Our purpose is to investigate the ability of different parametric forms to ‘correctly’ estimate consumer demands based on distance functions using Monte Carlo methods. Our approach combines economic theory, econometrics and quadratic approximation. We begin by deriving parameterizations for transformed quadratic functions which are linear in parameters and characterized by either homogeneity or which satisfy the translation property. Homogeneity is typical of Shephard distance functions and expenditure functions, whereas translation is characteristic of benefit/shortage or directional distance functions. The functional forms which satisfy these conditions and include both first- and second-order terms are the translog and quadratic forms, respectively. We then derive a primal characterization which is homogeneous and parameterized as translog and a dual model which satisfies the translation property and is specified as quadratic. We assess functional form performance by focusing on empirical violations of the regularity conditions. Our analysis corroborates results from earlier Monte Carlo studies on the production side suggesting that the quadratic form more closely approximates the ‘true’ technology or in our context consumer preferences than the translog.     

User,Use & Utility Research

Business and Information Systems Engineering (BISE) is at a turning point. Planning, designing, developing and operating IT used to be a management task of a few elites in public ad-ministrations and corporations. But the continuous digitization of nearly all areas of life changes the IT landscape fundamentally. Success in this new era requires putting the human perspective – the digital user – at the very heart of the new digitized service-led economy. BISE faces not just a temporary trend but a complex socio-technical phenomenon with far-reaching implications. The challenges are manifold and have major consequences for all stakeholders, both in information systems and management research as well as in practice. Corporate processes have to be re-designed from the ground up, starting with the user’s perspective, thus putting usage experience and utility of the individual center stage. The digital service economy leads to highly personalized application systems while organizational functions are being fragmented. Entirely new ways of interacting with information systems, in particular beyond desktop IT, are being invented and established. These fundamental challenges require novel approaches with regards to innovation and development methods as well as adequate concepts for enterprise or service system architectures. Gigantic amounts of data are being generated at an accelerating rate by an increasing number of devices – data that need to be managed. In order to tackle these extraordinary challenges we introduce ‘user, use & utility’ as a new field of BISE that focuses primarily on the digital user, his or her usage behavior and the utility associated with system usage in the digitized service-led economy. The research objectives encompass the development of theories, methods and tools for systematic requirement elicitation, systems design, and business development for successful Business and Information Systems Engineering in a digitized economy – information systems that digital users enjoy using. This challenge calls for leveraging insights from various scientific disciplines such as Design, Engineering, Computer Science, Psychology and Sociology. BISE can provide an integrated perspective, thereby assuming a pivotal role within the digitized service led economy.     

Benchmark Bonds Interactions under Regime Shifts

In the present paper we examine the interactions among five benchmark ten year government bonds, namely those of the USA, Germany, France, Italy and the Netherlands. Our aim is to illustrate empirically a net of interactions existing among the major bond markets of Europe and the US market taking into account shifts in the underlying stochastic processes. For this purpose, differing from the rest of the relevant empirical literature, after specifying the long run equilibrium relations we estimate the linkages between the bond markets as subject to hidden Markov chains, by applying the Markov Switching Vector Error Correction framework (MS‐VECM). This formulation is found to efficiently reflect the shifts brought about by significant economic events, such as the European monetary unification. As a result we illustrate different short‐run relations referring to the periods before and after the monetary union. Overall, our empirical results indicate that stronger interactions among the markets of the system exist in the period after the EMU. Also, by means of a variance decomposition analysis we assess leader‐follower relations which indicate that the benchmark status of bonds has changed since the introduction of the common monetary policy framework in Europe.     

Value at risk models for volatile emerging markets equity portfolios

This paper investigates the issue of market risk quantification for emerging and developed market equity portfolios. A very wide spectrum of popular and widely used in practice Value at Risk (VaR) models are evaluated and compared with Extreme Value Theory (EVT) and adaptive filtered models, during normal, crises, and post-crises periods. The results are interesting and indicate that despite the documented differences between emerging and developed markets, the most successful VaR models are common for both asset classes. Furthermore, in the case of the (fatter tailed) emerging market equity portfolios, most VaR models turn out to yield conservative risk forecasts, in contrast to developed market equity portfolios, where most models underestimate the realized VaR. VaR estimation during periods of financial turmoil seems to be a difficult task, particularly in the case of emerging markets and especially for the higher loss quantiles. VaR models seem to be affected less by crises periods in the case of developed markets. The performance of the parametric (non-parametric) VaR models improves (deteriorates) during post-crises periods due to the inclusion of extreme events in the estimation sample.     

Bidder Gains and Losses of Firms Involved in Many Acquisitions

Abstract:  We examine shareholders' wealth effects (both in the short- and the long-run) of UK frequent bidders acquiring public, private, and/or subsidiary targets with alternative methods of payment between 1987 and 2004. We find that, in the short-run, bidders break even when acquiring public targets and gain significantly when buying private and subsidiary targets. This result is robust after controlling for relative size, bidder's book-to-market ratio, target origin, and industry diversification. Our long-run evidence, however, reveals that acquirers experience, significant wealth losses regardless of the target type acquired, indicating that markets may initially overreact to the acquisition announcement. As a result, we argue that contrary to Fuller et al. (2002) who suggest that acquiring private and subsidiary firms creates value for bidding firms, a reliable conclusion on bidders' shareholders wealth effects cannot be based solely on a short-run event study.     

Subsampling the distribution of diverging statistics with applications to finance

In this paper we propose a subsampling estimator for the distribution of statistics diverging at either known or unknown rates when the underlying time series is strictly stationary and strong mixing. Based on our results we provide a detailed discussion of how to estimate extreme order statistics with dependent data and present two applications to assessing financial market risk. Our method performs well in estimating Value at Risk and provides a superior alternative to Hill's estimator in operationalizing Safety First portfolio selection.     

A multivariate Poisson mixture model for marketing applications

This paper describes a multivariate Poisson mixture model for clustering supermarket shoppers based on their purchase frequency in a set of product categories. The multivariate nature of the model accounts for cross-selling effects between the purchases made in different product categories. However, for computational reasons, most multivariate approaches limit the covariance structure by including just one common interaction term, or by not including any covariance at all. Although this reduces the number of parameters significantly, it is often too simplistic as typically multiple interactions exist on different levels. This paper proposes a theoretically more complete variance/covariance structure of the multivariate Poisson model, based on domain knowledge or preliminary statistical analysis of significant purchase interaction effects in the data. Consequently, the model does not contain more parameters than necessary, whilst still accounting for the existing covariance in the data. Practically, retail category managers can use the model to devise customized merchandising strategies.