THE DYNAMICS OF REAL EXCHANGE RATES: A RECONSIDERATION

In this paper we offer a bootstrap‐based version of the Cox specification test for non‐nested hypothesis to discriminate between ESTAR and MSAR models. Both models are commonly used for modeling real exchange rates dynamics. We show that the test has good size and power properties in finite samples. In an application, we analyze several major real exchange rates to shed light on the question of which model describes these processes best. This allows us to draw conclusions about the driving forces of real exchange rates. Copyright © 2013 John Wiley & Sons, Ltd.     

Robust Non‐nested Testing for Ordinary Least Squares Regression when Some of the Regressors are Lagged Dependent Variables*

The problem of testing non‐nested regression models that include lagged values of the dependent variable as regressors is discussed. It is argued that it is essential to test for error autocorrelation if ordinary least squares and the associated J and F tests are to be used. A heteroskedasticity–robust joint test against a combination of the artificial alternatives used for autocorrelation and non‐nested hypothesis tests is proposed. Monte Carlo results indicate that implementing this joint test using a wild bootstrap method leads to a well‐behaved procedure and gives better control of finite sample significance levels than asymptotic critical values.     

Methods for Scalar‐on‐Function Regression

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images and so on are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to this problem, categorising the basic model types as linear, non‐linear and non‐parametric. We discuss publicly available software packages and illustrate some of the procedures by application to a functional magnetic resonance imaging data set.     

Non‐Fundamentalness in Structural Econometric Models: A Review

Current economic theory typically assumes that all the macroeconomic variables belonging to a given economy are driven by a small number of structural shocks. As recently argued, apart from negligible cases, the structural shocks can be recovered if the information set contains current and past values of a large, potentially infinite, set of macroeconomic variables. However, the usual practice of estimating small size causal Vector AutoRegressions can be extremely misleading as in many cases such models could fully recover the structural shocks only if future values of the few variables considered were observable. In other words, the structural shocks may be non‐fundamental with respect to the small dimensional vector used in current macroeconomic practice. By reviewing a recent strand of econometric literature, we show that, as a solution, econometricians should enlarge the space of observations, and thus consider models able to handle very large panels of related time series. Among several alternatives, we review dynamic factor models together with their economic interpretation, and we show how non‐fundamentalness is non‐generic in this framework. Finally, using a factor model, we provide new empirical evidence on the effect of technology shocks on labour productivity and hours worked.     

Forecast Encompassing and Parameter Estimation*

A desirable property of a forecast is that it encompasses competing predictions, in the sense that the accuracy of the preferred forecast cannot be improved through linear combination with a rival prediction. In this paper, we investigate the impact of the uncertainty associated with estimating model parameters in‐sample on the encompassing properties of out‐of‐sample forecasts. Specifically, using examples of non‐nested econometric models, we show that forecasts from the true (but estimated) data generating process (DGP) do not encompass forecasts from competing mis‐specified models in general, particularly when the number of in‐sample observations is small. Following this result, we also examine the scope for achieving gains in accuracy by combining the forecasts from the DGP and mis‐specified models.     

Forecast Pooling for European Macroeconomic Variables*

We compare alternative forecast pooling methods and 58 forecasts from linear, time‐varying and non‐linear models, using a very large dataset of about 500 macroeconomic variables for the countries in the European Monetary Union. On average, combination methods work well but single non‐linear models can outperform them for several series. The performance of pooled forecasts, and of non‐linear models, improves when focusing on a subset of unstable series, but the gains are minor. Finally, on average over the EMU countries, the pooled forecasts behave well for industrial production growth, unemployment and inflation, but they are often beaten by non‐linear models for each country and variable.     

A score test for non‐nested hypotheses with applications to discrete data models

In this paper it is shown that a convenient score test against non‐nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. This is essentially a test for the correct specification of the conditional distribution of the variable of interest. Given its characteristics, the proposed test is particularly attractive to check the distributional assumptions in models for discrete data. The usefulness of the test is illustrated with an application to models for recreational boating trips. Copyright © 2001 John Wiley & Sons, Ltd.     

A new non‐randomized response model: The parallel model

Despite certain advances for non‐randomized response (NRR) techniques in the past 6 years, the existing non‐randomized crosswise and triangular models have several limitations in practice. In this paper, I propose a new NRR model, called the parallel model with a wider application range. Asymptotical properties of the maximum likelihood estimator (and its modified version) for the proportion of interest are explored. Theoretical comparisons with the crosswise and triangular models show that the parallel model is always more efficient than the two existing NRR models for most of the possible parameter ranges. Bayesian methods for analyzing survey data from the parallel model are developed. A case study on college students' premarital sexual behavior at Wuhan and a case study on plagiarism at the University of Hong Kong are conducted and are used to illustrate the proposed methods. © 2014 The Authors. Statistica Neerlandica © 2014 VVS.     

Modelling Electricity Prices: International Evidence*

This article analyses the evolution of electricity prices in deregulated markets. We present a general class of models that simultaneously takes into account several factors: seasonality, mean reversion, GARCH behaviour and time‐dependent jumps. The models are applied to daily equilibrium spot prices of eight electricity markets. Eight different nested models were estimated to compare the relative importance of each factor in each of the eight markets. We find strong evidence that electricity equilibrium prices are mean‐reverting, with volatility clustering (GARCH) and with jumps of time‐dependent intensity, even after adjusting for seasonality.     

Alternative Approaches to Multilevel Modelling of Survey Non‐Contact and Refusal

We review three alternative approaches to modelling survey non‐contact and refusal: multinomial, sequential, and sample selection (bivariate probit) models. We then propose a multilevel extension of the sample selection model to allow for both interviewer effects and dependency between non‐contact and refusal rates at the household and interviewer level. All methods are applied and compared in an analysis of household non‐response in the United Kingdom, using a data set with unusually rich information on both respondents and non‐respondents from six major surveys. After controlling for household characteristics, there is little evidence of residual correlation between the unobserved characteristics affecting non‐contact and refusal propensities at either the household or the interviewer level. We also find that the estimated coefficients of the multinomial and sequential models are surprisingly similar, which further investigation via a simulation study suggests is due to non‐contact and refusal having largely different predictors.     

Using the Fraction of Missing Information to Identify Auxiliary Variables for Imputation Procedures via Proxy Pattern‐mixture Models

In many surveys, imputation procedures are used to account for non‐response bias induced by either unit non‐response or item non‐response. Such procedures are optimised (in terms of reducing non‐response bias) when the models include covariates that are highly predictive of both response and outcome variables. To achieve this, we propose a method for selecting sets of covariates used in regression imputation models or to determine imputation cells for one or more outcome variables, using the fraction of missing information (FMI) as obtained via a proxy pattern‐mixture (PMM) model as the key metric. In our variable selection approach, we use the PPM model to obtain a maximum likelihood estimate of the FMI for separate sets of candidate imputation models and look for the point at which changes in the FMI level off and further auxiliary variables do not improve the imputation model. We illustrate our proposed approach using empirical data from the Ohio Medicaid Assessment Survey and from the Service Annual Survey.     

Combining Modelling Strategies to Analyse Teaching Styles Data

This paper combines two estimation procedures: Iterative Generalized Least Squares as used in the software MLwiN; Gibbs Sampling as employed in thesoftware BUGS to produce a modelling strategy that respects the hierarchical natureof the Teaching Styles data and also allows for the endogeneity problems encountered when examining pupil progress.     

Conditional heteroscedasticity of exchange rates: further results based on the fractionally integrated approach

A recent article (Tse, 1998 ) published in this journal analysed the conditional heteroscedasticity of the yen–dollar exchange rate based on the fractionally integrated asymmetric power ARCH model. In this paper, we present replication results using Tse's ( 1998 ) yen–dollar series. We also examine the robustness of Tse's ( 1998 ) findings across different currencies, sample periods and non‐nested GARCH‐type models. Unlike Tse ( 1998 ), we find some evidence of asymmetric conditional volatility for daily returns of currencies measured against the dollar or the yen. Copyright © 2004 John Wiley & Sons, Ltd.     

A Review of the Use of Conditional Likelihood in Capture‐Recapture Experiments

We present a modern perspective of the conditional likelihood approach to the analysis of capture‐recapture experiments, which shows the conditional likelihood to be a member of generalized linear model (GLM). Hence, there is the potential to apply the full range of GLM methodologies. To put this method in context, we first review some approaches to capture‐recapture experiments with heterogeneous capture probabilities in closed populations, covering parametric and non‐parametric mixture models and the use of covariates. We then review in more detail the analysis of capture‐recapture experiments when the capture probabilities depend on a covariate.     

Testing for Misspecification in Binary Response Models with Competing Distributions*

In empirical studies, the probit and logit models are often used without checks for their competing distributional specifications. It is also rare for econometric tests to be focused on this issue. Santos Silva [Journal of Applied Econometrics (2001 ), Vol. 16, pp. 577–597] is an important recent exception. By using the conditional moment test principle, we discuss a wide class of non‐nested tests that can easily be applied to detect the competing distributions for the binary response models. This class of tests includes the test of Santos Silva (2001 ) for the same task as a particular example and provides other useful alternatives. We also compare the performance of these tests by a Monte Carlo simulation.     

Placing the Urban Village: A Spatial Perspective on the Development Process of Urban Villages in Contemporary China

The rapid urbanization of China since the mid‐1980s has led to the development of a new spatial category, the urban village (chengzhongcun). The dominant neoliberal urban development regime approaches urban villages as a social, spatial, economic and political problem, and as targets for aggressive redevelopment and eradication policies. In this article, I propose a spatial perspective that makes use of several theoretical ‘anchors' to analyze the influence of urban village spatiality on its development process and to explore alternatives to the dominant redevelopment model. I begin by examining the spatial conceptualization of the urban village as a non‐place, arguing that this spatial reading undergirds the redevelopment‐by‐demolition model and tends to obscure alternative conceptualizations. I then move on to propose three alternative readings of urban village space, examining it as an everyday space, a liminal space and a neighborhood. Combining these three readings with the ‘non‐place' conceptualization provides a nuanced understanding of urban villages' unique spatial attributes and social roles, by evoking spatial and social processes that take place in most urban villages across China. Taken together, these spatial readings challenge the social and spatial rigidity of dominant representations of urban villages and supply a much‐needed spatially based conceptual framework that can be used to develop new urban planning models.     

The Impact of Standard Setting on Relevance and Reliability of Accounting Information: Lower of Cost or Market Accounting Reforms in China

During the period from 1998 to 2000, China implemented several new asset write‐down regulations that mandate lower of cost or market accounting (LCM) for most non‐cash assets. This is a study of the relevance and reliability of those regulations for investors in China. The study measures the association of net asset value with market value of equity and the association of accounting income with stock return, on both a historical cost accounting (HCA) basis and on an LCM basis. A fixed‐effects model controlling both year and firm effects is used in a balanced panel sample. The panel regressions show high levels of explanatory power. LCM values can be relevant but may be measured with sufficient error that they do not improve the prediction of firm values. Reliability is measured using non‐nested, overlapping model comparison tests (J and Cox). The paper also considers whether discretionary motivations influence the amount of write‐down. The study supports the relevance of LCM reforms, but finds that reliability is not increased over HCA during the period under study. Reliability appears to be reduced by the voluntary nature of LCM provisions during part of the period and by the effects of opportunism for some firms in the sample.     

Non‐competes,business dynamism,and concentration: Evidence from a Florida case study

Most research on non‐competes has focused on employees; here we study how non‐competes affect firm location choice, growth, and consequent regional concentration, using Florida's 1996 legislative change that eased restrictions on their enforcement. Difference‐in‐differences models show that following the change, establishments of large firms were more likely to enter Florida; they also created a greater proportion of jobs and increased their share of employment in the state. Entrepreneurs or establishments of small firms, in contrast, were less likely to enter Florida following the law change; they also created a smaller proportion of new jobs and decreased their share of employment. Consistent with these location and job creation dynamics, regional business concentration increased following the law change in Florida. Nationwide cross‐sections demonstrate consistent correlations between state‐level non‐compete enforcement and the location, employment, and concentration dynamics illustrated in Florida.