A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model

It is well known that the standard Breusch and Pagan (1980) LM test for cross-equation correlation in a SUR model is not appropriate for testing cross-sectional dependence in panel data models when the number of cross-sectional units (n)$\left(n\right)$ is large and the number of time periods (T)$\left(T\right)$ is small. In fact, a scaled version of this LM test was proposed by Pesaran (2004) and its finite sample bias was corrected by Pesaran et al. (2008). This was done in the context of a heterogeneous panel data model. This paper derives the asymptotic bias of this scaled version of the LM test in the context of a fixed effects homogeneous panel data model. This asymptotic bias is found to be a constant related to n$n$ and T$T$, which suggests a simple bias corrected LM test for the null hypothesis. Additionally, the paper carries out some Monte Carlo experiments to compare the finite sample properties of this proposed test with existing tests for cross-sectional dependence.     

Testing spatial regression models under nonregular conditions

In time series context, estimation and testing issues with autoregressive and moving average (ARMA) models are well understood. Similar issues in the context of spatial ARMA models for the disturbance of the regression, however, remain largely unexplored. In this paper, we discuss the problems of testing no spatial dependence in the disturbances against the alternative of spatial ARMA process incorporating the possible presence of spatial dependence in the dependent variable. The problems of conducting such a test are twofold. First, under the null hypothesis, the nuisance parameter is not identified, resulting in a singular information matrix (IM), which is a nonregular case in statistical inference. To take account of singular IM, we follow Davies (Biometrika 64(2):247–254, 1977; Biometrika 74(1):33–43, 1987) and propose a test procedure based on the supremum of the Rao score test statistic. Second, the possible presence of spatial lag dependence will have adverse effect on the performance of the test. Using the general test procedure of Bera and Yoon (Econom Theory 9:649–658, 1993) under local misspecification, we avoid the explicit estimation of the spatial autoregressive parameter. Thus our suggested tests are entirely based on ordinary least squares estimation. Tests suggested here can be viewed as a generalization of Anselin et al. (Reg Sci Urban Econ 26:77–104, 1996). We conduct Monte Carlo simulations to investigate the finite sample properties of the proposed tests. Simulation results show that our tests have good finite sample properties both in terms of size and power, compared to other tests in the literature. We also illustrate the applications of our tests through several data sets.     

Does microtherm boost pharmaceutical companies’ market capitalization returns?

The purpose of this study was to survey the relationship between the temperature factors and market capitalization returns of pharmaceutical companies by analysing both the daily and weekly frequency data in Taiwan. The threshold regression model with the GJR-GARCH process was applied for examination in this study; we found that pharmaceutical companies’ market capitalization returns could be boosted after exposure to extremely low temperatures for a period of time. Besides, the delayed effect of cold weather is demonstrated to exist. This phenomenon can be illustrated by epidemiological evidence-related mental factors, not by traditional behavioural finance. Moreover, lower weekly average temperatures are beneficial for investors to gain weekly pharmaceutical companies’ market capitalization returns. We are of the opinion that our findings offer an insightful suggestion for investors to buy pharmaceutical stocks at an opportune moment.     

Tariff and Quota Equivalence in Vertically Related Markets

This paper re‐examines the issue of tariff and quota equivalence by introducing an upstream market into the Hwang and Mai (1988 ) model, and then allowing the two downstream firms to cross‐haul within each other's market. We assume the upstream monopolist can select either a two‐part or a one‐part tariff pricing strategy. It is found that if the upstream firm adopts a two‐part (one‐part) tariff pricing strategy, then the market price of the final good under a tariff will be higher (lower) than that under an equivalent quota; that is, the quota is set at the import level under the tariff regime. This result stands in stark contrast to the prior findings of both Hwang and Mai (1988 ) and Fung (1989 ). Moreover, if the quota rent is set as being equal to the tariff revenue, the social welfare under a tariff will necessarily be lower than that under an equivalent quota.     

A re-examination of the impact of credit ratings and economic factors on state bond yields

In this article we re-examine the impact of credit ratings and economic factors on state bond yields using a two-step model. In the first step, we adopt an ordered probit technique to obtain consistent estimates of state bond default risk. In the second step, we estimate state bond risk premiums using a regression analysis with a categorized risk variable obtained from the first step. Similar to Terza (1987) and Hsiao (1983), the model involves a categorized ordinal explanatory (rating) variable. However, our two-step model deals with a case where category thresholds are unknown and dependent on economic factors. The model provides consistent estimates for the effects of ratings and economic factors on state bond yields. Contrary to previous findings, we find that state bond yields are mainly affected by fundamental economic variables.     

International R&D Spillovers: An Application of Estimation and Inference in Panel Cointegration

In this paper, we apply the asymptotic theory of panel cointegration developed by Kao and Chiang (1998) to Coe and Helpman's (1995) international R&D spillovers regression. The OLS with bias-correction, the fully-modified (FM) and the dynamic OLS (DOLS) estimations produce different predictions about the impact of foreign R&D on total factor productivity (TFP) although all the estimations support the result that domestic R&D is related to TFP.     

Data-driven tree structure for PIN models

Probability of informed trading (PIN) models characterize trading with certain types of information through a tree structure. Different tree structures with different numbers of groups for market participants have been proposed, with no clear, consistent tree used in the literature. One of the main causes of this inconsistency is that these trees are artificially proposed through a bottom-up approach rather than implied by actual market data. Therefore, in this paper, we propose a method that infers a tree structure directly from empirical data. More precisely, we use hierarchical clustering to construct a tree for each individual firm and then infer an aggregate tree through a voting mechanism. We test this method on US data from January 2002 for 7608 companies, which results in a tree with two layers and four groups. The characteristics of the resulting aggregate tree are between those of several proposed tree structures in the literature, demonstrating that these proposed trees all reflect only part of the market, and one should consider the proposed empirically driven method when seeking a tree representing the whole market.

     

Effect of collateral characteristics on bank performance: Evidence from collateralized stocks in Taiwan

Taiwanese law requires directors of listed firms to disclose their stocks collateralized at banks creating the possibility of examining the characteristics of collateralized stocks and their influence on bank performance. This study demonstrates that the risk (value) attributes of collateralized stocks increase (reduce) bank efficiency yet reduce (increase) bank profits. Government-owned banks but not private banks require sufficiently high margins to prevent stock loans from non-performing. Furthermore, banks charge higher interest to cover the non-performing risk. Directors who lack funds, hold high turnover stocks, and/or have weak relationships with their banks prefer to collateralize their stocks at private banks.     

Co-opted directors,gender diversity,and crash risk: evidence from China

Review of Quantitative Finance and Accounting - This study examines how the composition of the board of directors at Chinese firms affects crash risk. The results indicate that co-opted directors...     

Has SOX Enhanced Non–Big 4 Auditors' Ability to Deal with Client Pressure?

We investigate whether non–Big 4 auditors have enhanced their ability to resist client pressure over accrual reporting following the Sarbanes‐Oxley Act (SOX). Regressing abnormal accruals on proxies for economic bonding, we find that changes in the association, defined as (Post–Pre), are significantly negative, implying an improvement in auditor independence after SOX. Among non–Big 4 auditors, only Tier 3 auditors compromised reporting objectivity before SOX, but neither Tier 2 nor Tier 3 auditors yielded to client pressure after SOX. Evidence that these two groups of non–Big 4 auditors differ in the way they cope with client pressure in a loose regulatory regime highlights the importance of assessing the efficacy of SOX separately for subsets of auditors and contributes to an understanding of the underresearched, but inherently important, segment of the audit market served by non–Big 4 auditors. Further analysis indicates that the low pre‐SOX audit quality observed in the full sample is driven by non–PCAOB registrants.