Evolution of indigenous tourism among the Lacandon of Chiapas: an application of Weaver’s model

ABSTRACT

In this paper, Weaver’s six-stage indigenous tourism model is applied to the Lacandon Maya (Hach Winik) of Chiapas, Mexico. Based on a comprehensive review of the anthropological and historical literature on this indigenous group, combined with longitudinal ethnographic and collaborative research performed with tourism entrepreneurs, the Lacandon tourism experience is assessed from the pre-European period until present. By analysing a case study of indigenous tourism in Mexico, a developing country in another geographical region and with a different colonial past, this work supplements Weavers’ perspective. The results show that the fourth and fifth stages of Weaver’s model coincide in this case study, while the sixth stage is still incomplete. Although the Lacandon case has its peculiarities and bearing in mind that several different factors should be considered in the Latin American context, the model proves to be an interesting tool for indigenous tourism analysis in developing countries.     

Inter-enterprise arrears in economies in transition

In the context of economies in transition, the paper argues that an excessive liquidity squeeze could throw the economy into a persistent state of low economic activity. In such bad equilibrium, enterprise transactions become largely demonetized, with a chain of arrears, a form of involuntary credit, spreading over the entire system. The empirical analysis of the Romanian experience seems to support the view advanced in the paper.     

Geometrical Interpretation of the Mean and the Constant in a Box-Jenkins Time Series Model

Certain manuals and computer programs mistakenly identify the mean with the constant in Box-Jenkins time series models. In this paper, it will be shown that (a) the mean and the constant have different values in autoregressive models, and (b) they have an algebraic and graphical relationship.     

Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting

Factor models have been applied extensively for forecasting when high‐dimensional datasets are available. In this case, the number of variables can be very large. For instance, usual dynamic factor models in central banks handle over 100 variables. However, there is a growing body of literature indicating that more variables do not necessarily lead to estimated factors with lower uncertainty or better forecasting results. This paper investigates the usefulness of partial least squares techniques that take into account the variable to be forecast when reducing the dimension of the problem from a large number of variables to a smaller number of factors. We propose different approaches of dynamic sparse partial least squares as a means of improving forecast efficiency by simultaneously taking into account the variable forecast while forming an informative subset of predictors, instead of using all the available ones to extract the factors. We use the well‐known Stock and Watson database to check the forecasting performance of our approach. The proposed dynamic sparse models show good performance in improving efficiency compared to widely used factor methods in macroeconomic forecasting. Copyright © 2014 John Wiley & Sons, Ltd.     

Markov-switching dynamic factor models in real time

We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as mixed sampling frequencies and ragged-edge data. First, we evaluate the theoretical gains of using data that are available promptly for computing probabilities of recession in real time. Second, we show how to estimate the model that deals with unbalanced panels of data and mixed frequencies, and examine the benefits of this extension through several Monte Carlo simulations. Finally, we assess its empirical reliability for the computation of real-time inferences of the US business cycle, and compare it with the alternative method of forecasting the probabilities of recession from balanced panels.     

Extracting Nonlinear Signals from Several Economic Indicators

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one‐step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two‐step approach). Second, we examine the role of increasing the number of indicators. Our results suggest that one step is generally preferred to two steps, especially in the vicinity of turning points, although its gains diminish as the quality of the indicators increases. Additionally, we also obtain decreasing returns of adding more indicators with similar signal‐to‐noise ratios. Using the four constituent series of the Stock–Watson coincident index, we illustrate these results for US data. Copyright © 2014 John Wiley & Sons, Ltd.     

Public–private wage gap in Latin America (1992–2007): A matching approach

Using matching methods, we estimate the public–private wage gap for urban workers in eleven Latin American countries for the 1992–2007 period. These methods do not require any estimation of earnings equations and hence no validity-out-of-the-support assumptions; furthermore, this approach allows us to estimate not only the average wage gap but also its distribution. Our main findings indicate that the average public sector worker earns more than his/her private counterpart, and that this differential increased over the 1992–2007 period. Important differences along the wage distribution are also shown in the results; in fact, public servants in the highest percentiles of the wage distribution generally earn less than their private sector equivalents. Nonetheless, the percentile at which a positive wage gap becomes a wage penalty shifted over the period as the average wage gap experienced by most countries widened. Still, the most qualified public sector workers do face a wage penalty. Furthermore, indicators of government effectiveness show no relationship with the country ranking according to the public–private wage gap.     

Financial crises and liquidity shocks a bank-run perspective

In contrast with the financial multiplier literature, this note explores a case in which the shock triggering a financial crisis stems from the financial sector itself; it is not a shock stemming from the real sector which gets amplified by, say, agency problems. The basic intuition is provided by the bank-run literature of the Diamond and Dybvig (1983) variety. Financial development is modeled as a mechanism that endows real assets (e.g., land and capital) with liquidity. However, liquidity can be impaired by shocks that are equivalent to a bank run. Liquidity creation enhances real asset prices, while a liquidity crunch generates asset price collapse. This bubble-looking episode is not driven by standard fundamentals, although it is fully in line with rationality. In this context, devoid of other frictions like price stickiness, the note examines the effect of monetary policy in the absence of nominal rigidities. It shows that preventing price deflation is not enough to offset relative (to output) asset price meltdown, but lower policy interest rates increase relative asset prices and steady-state output. Moreover, in the neighborhood of a first-best capital allocation, an increase in the liquidity of capital may lower the welfare of the representative individual, even if the higher liquidity of capital is sustainable and, hence, not destroyed by future crash – illustrating the possibility of “excessive” financial innovation. An extension of the basic model supports the conjecture that low policy interest rates may have given further incentives to the development of “shadow banking.”     

What Prevents Firms from Advancing in their Environmental Strategy?

The aim of this paper is to analyze the determinants of the strategic environmental behavior of firms and, more specifically, the external and internal barriers that limit and sometimes even prevent the environmental adaptation. The analysis focuses on a sample of industrial firms that have at least three workers and that are located in Aragón, a region situated in the northeast of Spain. In order to achieve this objective, first the theoretical literature on the topic is reviewed. Subsequently, from the firms which were sampled, the existence of an underlying structure among the totality of barriers is studied. Finally, this structure is analyzed in order to determine if it has any influence on the degree of proactivity of the firm’s environmental strategy.