Dynamic Entry and Exit Linkages in the Brazilian Manufacturing Industry: An Econometric Investigation

The paper investigates dynamic linkages between entry and exit rates in Brazilian manufacturing in the context of 231 (four-digit) industries during the 1996–2005 period. The empirical analysis focuses on the estimation of a dynamic panel data model for entry and exit rates, and controls for the business cycle and structural characteristics, such as industrial concentration and suboptimal scale. The empirical evidence is partially consistent with a multiplier effect where synergetic factors prevail by exit inducing exit. Evidence partially supports a competition effect that could be related to a selection process favoring efficiency, as exit induces entry. The business cycle control variable and the aforementioned structural variables appear to play no role in delineating entry and exit linkages. The results are similar, although not identical, to previous evidence for developed countries.     

Entrepreneurial capacities as antecedents of business performance in Brazilian firms

We investigate the relationship between entrepreneurial capacities and firm performance. More specifically, we investigate the effects of radical innovation and learning orientation on business performance. We test the effects of entrepreneurial orientation on learning orientation and radical innovation. The results suggest that radical product innovation and companies' orientation to learn have a positive effect on organizational performance. Additionally, we find that entrepreneurial orientation positively influences a firm's capability to learn and innovate. Our findings also show a direct effect of learning orientation on radical innovation, which means that companies with a higher proclivity to learn are more likely to create products and processes, representing a major departure from the state of current knowledge. Copyright © 2014 ASAC. Published by John Wiley & Sons, Ltd.     

Informality,Size and Regulation: Theory and an Application to Egypt

The paper shows how, when the enforceability of regulationsis size-sensitive, price competition can lock firms into informality and,thus, smallness, depending on the form of the production function. In thatcontext, exogenous "help" packages targeted to informal firms "promote"micro and small enterprises (i.e., increase their numbers) but do not"develop" them (i.e., foster their growth). The "help" only generates ashort-term span of abnormal profits for existing informal firms, and a long-term income transfer toward informal-market consumers. The model istested in the context of Egypt's micro and small enterprise sector.     

AGOA and Apparel: Who Captures the Tariff Rent in the Presence of Preferential Market Access?

The United States grants preferential (tariff‐ and quota‐free) market access to a list of products from eligible countries in sub‐Saharan Africa through the African Growth and Opportunity Act (AGOA). We analyse the increase in prices received by apparel exporters who benefited from AGOA preferences. In the presence of competitive markets, export prices should increase as much as the tariff which was previously collected by the US government. We refer to this price increase as the ‘tariff preference rent’ since exporters receive this income as the rent for their preferential status. The results show that exporters receive only one‐third of this rent and smaller exporters receive less than larger and established ones. We then provide evidence that suggests this may be due to the degree of market power enjoyed by US importers when facing African exporters.     

Poisson–geometric INAR(1) process for modeling count time series with overdispersion

In this paper, we propose a new first‐order non‐negative integer‐valued autoregressive [INAR(1)] process with Poisson–geometric marginals based on binomial thinning for modeling integer‐valued time series with overdispersion. Also, the new process has, as a particular case, the Poisson INAR(1) and geometric INAR(1) processes. The main properties of the model are derived, such as probability generating function, moments, conditional distribution, higher‐order moments, and jumps. Estimators for the parameters of process are proposed, and their asymptotic properties are established. Some numerical results of the estimators are presented with a discussion of the obtained results. Applications to two real data sets are given to show the potentiality of the new process.     

Testing the Markov property with high frequency data

This paper develops a framework to nonparametrically test whether discrete-valued irregularly spaced financial transactions data follow a Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates the irregular spacing that characterizes transactions data. Under such an observation rule, the current price duration is independent of a previous price duration given the previous price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Monte Carlo simulations suggest that the asymptotic test has huge size distortions, though a bootstrap-based variant entails reasonable size and power properties in finite samples. As for an empirical illustration, we investigate whether bid–ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid–ask spread. We robustly reject the Markov assumption for two out of the five stocks under scrutiny. Finally, it is reassuring that our results are consistent with two alternative measures of asymmetric information.     

An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals

In this paper we provide an alternative approach to analyze the demand for international tourism in the Balearic Islands, Spain, by using a neural network model that incorporates time-varying conditional volatility. We consider daily air passenger arrivals to Palma de Mallorca, Ibiza and Mahon, which are located in the islands of Mallorca, Ibiza and Menorca, respectively, as a proxy for international tourism demand for the Balearic Islands. Spain is a world leader in terms of total international tourist arrivals and receipts, and Mallorca is one of the most popular destinations in Spain. For tourism management and marketing, it is essential to forecast high frequency international tourist demand accurately. As it is important to provide sensible international tourism demand forecast intervals, it is also necessary to model their variances accurately. Moreover, time-varying variances provide useful information regarding the risks associated with variations in international tourist arrivals.     

Evaluating the risk premium in the U.S.A. natural gas market: evidence from low-price regime

In recent years, the U.S.A. natural gas market has seen enormous changes. The expectations of abundant supply of shale gas and the slow U.S.A. economic recovery have pushed gas prices below US$ 4 MMBtu. Although shale gas is a new promising source of unconventional energy, investors face uncertain investment plans. In this study, we investigate the risk premium by comparing behaviour before and after the change point in agents risk perception. Unlike traditional empirical research on risk premium, we use the parametric, two-factor model of Schwartz and Smith (2000) to evaluate the implied risk premium term structure from futures prices traded on the New York Mercantile Exchange (NYMEX). We compare our findings with other empirical results and find that the change point lies at the beginning of the low-price regime. When we compare periods before and after the change point, we observe that the risk premium changed, not only in sign, but also in magnitude.