Interpretation problems of the partial correlation with nonnormally distributed variables

The partial correlation is a commonly used measure for assessing the bivariate correlation of two quantitative variables after eliminating the influence of one or more other variables. The partial correlation is generally interpreted as the correlation that would result if the variables to be eliminated were fixed (not allowed to vary and influence the other variables), which is referred to in the statistical literature as conditional correlation. The present paper demonstrates, by means of theoretical derivations and practical examples, that when the assumption of multivariate normality is violated (e.g., as a result of nonlinear relationships among the variables investigated) the usual interpretation of the partial correlation coefficient will be basically incorrect. In extreme cases the value of the partial correlation coefficient may be strongly positive, close to 1, whereas the conditional correlation may have a large negative value. To solve this problem the paper suggests to partial out a certain function (in most cases the square) of the variables whose effects are to be eliminated if nonlinear relationships are likely to occur.     

HEGY Tests in the Presence of Moving Averages*

We analyze the asymptotic distributions associated with the seasonal unit root tests of Hylleberg et al. (1990) for quarterly data when the innovations follow a moving average process. Although both the t‐ and F‐type tests suffer from scale and shift effects compared with the presumed null distributions when a fixed order of autoregressive augmentation is applied, these effects disappear when the order of augmentation is sufficiently large. However, as found by Burridge and Taylor (2001) for the autoregressive case, individual t‐ratio tests at the semi‐annual frequency are not pivotal even with high orders of augmentation, although the corresponding joint F‐type statistic is pivotal. Monte Carlo simulations verify the importance of the order of augmentation for finite samples generated by seasonally integrated moving average processes.     

Restricted forecasting with VAR models: An analysis of a test for joint compatibility between restrictions and forecasts

A restricted forecasting compatibility test for Vector Autoregressive Error Correction models is analyzed in this work. It is shown that a variance–covariance matrix associated with the restrictions can be used to cancel out model dynamics and interactions between restrictions. This allows us to interpret the joint compatibility test as a composition of the corresponding single restriction compatibility tests. These tests are useful for appreciating the contribution of each and every restriction to the joint compatibility between the whole set of restrictions and the unrestricted forecasts. An estimated process adjustment for the test is derived and the resulting feasible joint compatibility test turns out to have better performance than the original one. An empirical illustration of the usefulness of the proposed test makes use of Mexican macroeconomic data and the targets proposed by the Mexican Government for the year 2003.     

Controlling the Urban Fabric: The Complex Game of Distance and Proximity in European Upper‐Middle‐Class Residential Strategies

This article presents an open discussion of the processes of urban secession and gentrification in contemporary European cities, arguing that intergroup social dynamics in urban spaces are generally more complex than either extreme mutual avoidance or the colonization of neighbourhoods by the wealthiest groups. We analyse the residential strategies of urban upper‐middle class managers in various European metropolitan areas through in‐depth semi‐structured interviews to argue that these groups develop complex strategies of proximity and distance in relation to other social groups. The development of these ‘partial exit’ strategies takes place through specific combinations of practices that allow groups to select the dimensions they are willing to share with other social groups, and those in which they prefer a more segregated social environment for themselves and their families. The responses of our interviewees were consistently more nuanced and complex than suggested by a simplistic theory about their drive to withdraw from society, forcing us to develop more sophisticated conceptual frameworks to account for the growing prevalence of multi‐layered identities and spheres of reference and solidarity, specific combinations of elective segregation and local involvement, and more active patterns of mobility combined with local embeddedness.     

Are Sunk Costs a Barrier to Entry?

The received wisdom is that sunk costs create a barrier to entry—if entry fails, then the entrant, unable to recover sunk costs, incurs greater losses. In a strategic context where an incumbent may prey on the entrant, sunk entry costs have a countervailing effect: they may effectively commit the entrant to stay in the market. By providing the entrant with commitment power, sunk investments may soften the reactions of incumbents. The net effect may imply that entry is more profitable when sunk costs are greater.     

Measurement of Variables Involved in the Design of a Training Study: Practical Experience Undertaken in a Sports Organisation

This article describes the process for preparing a survey, which will be used to measure relevant variables, which are involved in a study of training needs in a Spanish sports organisation. The variables which have been considered are: problems and difficulties in carrying work of specific positions; “strong points” in carrying out this work; usefulness of the training received in facing and solving the above-mentioned problems and difficulties; usefulness of the training received in acquiring and strengthening these “strong points” in carrying out work; opinion and suggestions with respect to future training. Due to the applied nature of the study, a data collection methodology was designed which was based on interviews and group discussions with a representative sample of workers. Finally, the predictive capacity of perception, which workers have, of their motivation at work was clearly shown in order to then identify different attitude and conduct patterns.     

Longitudinal analysis of entrepreneurship and competitiveness dynamics in Latin America

This study analyzes the relationship between entrepreneurial dynamics in Latin-American countries and the level of competitiveness these countries show. Based on the research conducted by Wennekers et al. [Small Business Economics, 24(3):293–309, 2005] that demonstrates a U-shaped relationship between the country’s rate of entrepreneurship and its level of competitiveness and economic development, we hypothesize that Latin-American countries have a descending behaviour under the U-shaped curve approach. The results from three regression models support this hypothesis and suggest that competitiveness and economic growth deter entrepreneurial dynamics on Latin-American countries. We discuss that Latin-American countries need to improve some structural factors to achieve a high level of entrepreneurial dynamics.

Output gap in Brazil: a real-time data analysis

Recent literature for developed economies has shown that output gap estimates go through important revisions over time, impairing their reliability in real time. We organize a real-time data set for Brazil’s GDP and assess the revisions of the output gap estimated by four different methods. Similar to the findings of studies for developed economies, the output gap revisions in Brazil are substantial in all methods, with frequent changes in the output gap sign. In general, both the GDP data revision and the effect of adding new observations to the sample are relevant sources of output gap revisions. However, differently from those studies, we cannot assert that the latter source is preponderant.     

Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project

This article brings together the stochastic frontier framework with impact evaluation methodology to compare technical efficiency (TE) across treatment and control groups using cross-sectional data associated with the MARENA Program in Honduras. A matched group of beneficiaries and control farmers is determined using propensity score matching techniques to mitigate biases stemming from observed variables. In addition, possible self-selection arising from unobserved variables is addressed using a selectivity correction model for stochastic frontiers recently introduced by Greene (J Prod Anal 34:15?C24, 2010). The results reveal that average TE is consistently higher for beneficiary farmers than the control group while the presence of selectivity bias cannot be rejected. TE ranges from 0.67 to 0.75 for beneficiaries and from 0.40 to 0.65 for the control depending on whether biases were controlled or not. The TE gap between beneficiaries and control farmers decreases by implementing the matching technique and the sample selection framework decreases this gap even further. The analysis also suggests that beneficiaries do not only exhibit higher TE but also higher frontier output.