A simple test for nonstationarity in mixed panels with incidental trends

Ng (2008) shows how the cross-sectional variance of the observed panel data can be used to construct a simple test for the proportion of non-stationary units. However, in the case with incidental trends the test is distorted. The present note shows how the distortions can be substantially reduced by the use of bias-adjustment. It also investigates the local power of the bias-adjusted test, which is shown to suffer from the same incidental trends problem previously only documented for conventional t-tests.

Testing slope homogeneity in large panels with serial correlation

Pesaran and Yamagata (Pesaran, M.H., Yamagata, T., Testing slope homogeneity in large panels, Journal of Econometrics 142, 50-93, 2008) propose a test for slope homogeneity in large panels, which has become very popular in the literature. However, the test cannot deal with the practically relevant case of heteroskedastic and/serially correlated errors. The present note proposes a generalized test that accommodates both features. © 2013 Elsevier B.V.

A note on the pooling of individual panic unit root tests

One of the most cited studies in recent years within the field of nonstationary panel data analysis is that of Bai and Ng (2004), in which the authors propose PANIC, a new framework for analyzing the nonstationarity of panels with idiosyncratic and common components. The problem is that the asymptotic validity of PANIC as a platform for constructing pooled panel unit root tests based on averaging is not fully proven. This paper provides the required results, whose usefulness is verified through simulations. © 2009 Cambridge University Press.

A simple test for cointegration in dependent panels with structural breaks

This paper develops a very simple test for the null hypothesis of no cointegration in panel data. The test is general enough to allow for heteroskedastic and serially correlated errors, unit-specific time trends, cross-sectional dependence and unknown structural breaks in both the intercept and slope of the cointegrated regression, which may be located at different dates for different units. The limiting distribution of the test is derived, and is found to be normal and free of nuisance parameters under the null. A small simulation study is also conducted to investigate the small-sample properties of the test. In our empirical application, we provide new evidence concerning the purchasing power parity hypothesis. © Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2008.

Pooled unit root tests in panels with a common factor

This paper proposes new pooled panel unit root tests that are appropriate when the data exhibit cross-sectional dependence that is generated by a single common factor. Using sequential limit arguments, we show that the tests have a limiting normal distribution that is free of nuisance parameters and that they are unbiased against heterogenous local alternatives. Our Monte Carlo results indicate that the tests perform well in comparison to other popular tests that also presumes a common factor structure for the cross-sectional dependence.

New empirical evidence on the bid-ask spread

In this article, we model the determinants of spread for 734 firms listed on the NYSE over the period 1 January 1998 to 31 December 2008. We propose a panel data model of the determinants of spread. There are four main messages emerging from our work. We find a statistically significant effect of volume on spread inconsistent with the work of Johnson (2008). On price, we find mixed results, consistent with the literature. On the effect of price volatility on spread, our results are completely the opposite of the cross-sectional literature but sides with the relatively recent work of Chordia et al. (2001). We allow for persistence of spread as a determinant of spread and find significant evidence of spread persistence across all 16 sectors. Finally, we examine size effects and find statistically strong evidence of size effects based on the relationship between price and spread, persistence and spread, and volatility and spread.

Capital structure and corporate performance: evidence from Jordan

This study is to investigate the effect which capital structure has had on corporate performance using a panel data sample representing of 167 Jordanian companies during 1989-2003. Our results showed that a firm’s capital structure had a significantly negative impact on the firm’s performance measures, in both the accounting and market’s measures. We also found that the short-term debt to total assets (STDTA) level has a significantly positive effect on the market performance measure (Tobin’s Q). The Gulf Crisis 1990-1991 was found to have a positive impact on Jordani an corporate performance while the out break of Intifadah in the West Bank and Gaza in September 2000 had a negative impact on corporate performance.

Default probability for the Jordanian companies: A test of cash flow theory

Abstract
This paper aims to investigate the effect of cash flow and free cash flow on corporate failure in the emerging market in particular Jordan using two samples; matched sample and a cross sectional time-series (panel data) sample representative of 167 Jordanian companies in 1989-2003. LOGIT models are used to outline the relationship between firms’ financial health and the probability of default. Our results show that there is firm’s free cash flow increases corporate failure. The result also shows that the firm’s cash flow decreases corporate failure. Firms’ capital structures are fund a mental in predicting default. Capital structure is seen as the main factor affecting the probability of default as it affects a firm’s ability to access external sources of funds. Jordanian firms depend on short-term debt for both short and long term financing.

A nonparametric model of financial system and economic growth

In this paper, we show that in the proposed models for economic growth, the financial system variables are generally nonparametric. We, thus, use a nonparametric panel data model to estimate the financial system-economic growth relationship. Our results suggest that as long as a country's domestic credit and private credit are above their cross-sectional mean they have a positive effect on GDP growth. We also discover that market capitalisation positively and significantly impacts GDP growth, while stocks traded (with the exception of OECD countries) has a statistically insignificant effect on GDP growth.

An explanation of capital structure of China's listed property firms

Purpose– The purpose of this paper is to investigate the determinants of the capital structure of listed property firms in China.Design/methodology/approach– The study is based on quantitative methods such as dynamic panel data models and a panel data set containing financial and accounting data for all listed property companies from 2006 to 2010 in China.Findings– The findings confirm that the state-own shares, the fixed asset values, the total size of assets and profitability have a positive and significant impact on the leverage ratio of listed property firms in China. The negative impact of the tax shields and the currency ratio, and significant impact of state-own shares on capital structure cannot be explained by existing capital structure theory but the unique property market regulation environment and market conditions in China.Research limitations/implications– The findings confirm the applicability of trade-off theory (except for the correlation between leverage and the tax shield) on property companies in China. They also highlight the importance of government policies and special market conditions in explaining the financing behaviour of property companies in transaction countries like China.Practical implications– Complimentary policies should be established along with property market restriction policies to offset their unequal negative effect on property companies with less state-owned shares. Furthermore, government should invest efforts to eliminate the discrimination credit treatment of banks against property companies with non-existent or few state-owned shares.Originality/value– The special financial behaviour of China's property firms and the unique financial and property market conditions highlight the necessity of researching the capital structure of listed property firms in China. However, most of the existing literature focuses on the company financial behaviour in developed countries, and very few studies have been done concerning property firms’ financing behaviour in emerging economies such as China, and this research prospects to fill this blank.

Agriculture, trade openness and emissions: an empirical analysis and policy options

This article investigates the impact of sectoral production allocation, energy usage patterns and trade openness on pollutant emissions in a panel consisting of high-, medium- and low-income countries. Extended STIRPAT (Stochastic Impact by Regression on Population, Affluence and Technology) and EKC (Environmental Kuznets Curve) models are conducted to systematically identify these factors driving CO2 emissions in these countries during the period 1980–2010. To this end, the studyemploys three different heterogeneous, dynamic mean group-type linear panel modelsand one nonlinear panel data estimation procedure that allows for cross-sectionaldependence. While affluence, nonrenewable energy consumption and energy intensity variables are found to drive pollutant emissions in linear models, population is also found to be a significant driver in the nonlinear model. Both service sector and agricultural value-added levels play a significant role in reducing pollution levels, whereas industrialisation increases pollution levels. Although the linear model fails totrack any significant impact of trade openness, the nonlinear model finds trade liberalisation to significantly affect emission reduction levels. All of these results suggest that economic development, and especially industrialisation strategies and environmental policies, need to be coordinated to play a greater role in emission reduction due to trade liberalisation.

A random coefficient approach to the predictability of stock returns in panels

© The Author, 2014. Most studies of the predictability of returns are based on time series data, and whenever panel data are used, the testing is almost always conducted in an unrestricted unit-by-unit fashion, which makes for a very heavy parametrization of the model. On the other hand, the few panel tests that exist are too restrictive in the sense that they are based on homogeneity assumptions that might not be true. As a response to this, the current study proposes new predictability tests in the context of a random coefficient panel data model, in which the null of no predictability corresponds to the joint restriction that the predictive slope has zero mean and variance. The tests are applied to a large panel of stocks listed at the New York Stock Exchange. The results suggest that while the predictive slopes tend to average to zero, in case of book-to-market and cash flow-to-price the variance of the slopes is positive, which we take as evidence of predictability.

A simple test for nonstationarity in mixed panels: A further investigation

The test of Ng (2008) is one of the few that enables general inference regarding the proportion of non-stationary units in panel data. The current paper furthers the investigation of Ng (2008) in two directions. First, the existing sequential limit analysis is generalized to a very flexible asymptotic framework in which the number of time periods, T, can be either fixed or tending to infinity jointly with the number of cross-section units, N. Second, the test statistic is evaluated not only under the null hypothesis, but also under alternatives that can be either fixed or local.

A Bayesian nonparametric approach to multilevel regression

Regression is at the cornerstone of statistical analysis. Multilevel regression, on the other hand, receives little research attention, though it is prevalent in economics, biostatistics and healthcare to name a few. We present a Bayesian nonparametric framework for multilevel regression where individuals including observations and outcomes are organized into groups. Furthermore, our approach exploits additional group-specific context observations, we use Dirichlet Process with product-space base measure in a nested structure to model group-level context distribution and the regression distribution to accommodate the multilevel structure of the data. The proposed model simultaneously partitions groups into cluster and perform regression. We provide collapsed Gibbs sampler for posterior inference. We perform extensive experiments on econometric panel data and healthcare longitudinal data to demonstrate the effectiveness of the proposed model

Exchange rate regimes and fiscal discipline: the role of trade openness

This study revisits the relationship between exchange rate regime (ERR) choice and fiscal discipline focusing on the role of trade openness. The conventional theoretical view is that fixed regimes bring about more fiscal discipline, while the recent literature argues that flexible regimes are more disciplinary. Empirical studies have provided mixed evidence. Using a panel dataset for a large number of developing and developed countries, as well as pooled panel OLS and instrumental variables (IV) estimation techniques, we find support for both views. We document that a fixed ERR is disciplinary at low levels of trade openness, while a flexible regime produces a greater fiscal discipline above a certain level of trade openness. Moreover, this relationship applies to only developing countries. These findings remain robust across different measures of fiscal outcomes, a number of controls, across different sub-samples, and are supported by both annual and five-year averaged panel data.