Post-Earnings Announcement Drift in Spain and Behavioural Finance Models

Our study examines whether behavioural theories can explain post-earnings announcement drift (i.e. earnings momentum) in the Spanish market. In particular, we test models proposed by Barberis et al. (Journal of Financial Economics, 49, pp. 307–343, 1998), Daniel et al. ( Journal of Finance, 53(6), pp. 1839–1885, 1998) and Hong and Stein (Journal of Finance, 54(6), pp. 2143–2184, 1999). Each of these behavioural models draws on two premises – cognitive biases and limits to arbitrage – that we assume will vary with a given country's cultural and institutional features. Therefore, we must exercise caution when extrapolating the favourable results observed in the US market to markets outside of the USA. Our results provide little evidence in support of the hypothesis used to test whether these models can indeed explain the earnings momentum anomaly in the Spanish market. We believe some characteristics of the Spanish market, such as its lower score on the Individualism Index, lower levels of investor protection and code-law-based legal system, may explain why our results differ from those obtained in the USA.     

ESTIMATION OF TIME‐VARYING ADJUSTED PROBABILITY OF INFORMED TRADING AND PROBABILITY OF SYMMETRIC ORDER‐FLOW SHOCK

Recently, Duarte and Young (2009) studied the probability of informed trading (PIN) proposed by Easley et al. (2002) and decomposed it into two parts: the adjusted PIN (APIN) as a measure of asymmetric information and the probability of symmetric order‐flow shock (PSOS) as a measure of illiquidity. They provide some cross‐section estimates of these measures using daily data over annual periods. In this paper we propose a method to estimate daily APIN and PSOS by extending the method in Tay et al. (2009) using high‐frequency transaction data. Our empirical results show that while PIN is positively contemporaneously correlated with variance, APIN is not. On the other hand, PSOS is positively correlated with daily average effective spread and variance, which is consistent with the interpretation of PSOS as a measure of illiquidity. Compared to APIN, PSOS exhibits clustering and sporadic bursts over time. Copyright © 2012 John Wiley & Sons, Ltd.     

Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis

In this article, we investigate the behaviour of stationarity tests proposed by Müller [Journal of Econometrics (2005) Vol. 128, pp. 195–213] and Harris et al. [Econometric Theory (2007) Vol. 23, pp. 355–363] with uncertainty over the trend and/or initial condition. As different tests are efficient for different magnitudes of local trend and initial condition, following Harvey et al. [Journal of Econometrics (2012) Vol. 169, pp. 188–195], we propose decision rule based on the rejection of null hypothesis for multiple tests. Additionally, we propose a modification of this decision rule, relying on additional information about the magnitudes of the local trend and/or the initial condition that is obtained through pre‐testing. The resulting modification has satisfactory size properties under both uncertainty types.     

Accounting for the Political Uncertainty Factor

We build our analysis upon previous work by Bloom et al. (Measuring the Effect of Political Uncertainty. Working Paper, Stanford University, 2012) and Baker et al. (Political Uncertainty: A New Indicator. CentrePiece 2012; 16 (3): 21–23), who estimate the dynamic effects of a shock to a newly constructed surrogate measure of political uncertainty (PU) on the US economy. Comparable to their results we demonstrate that a shock to PU has pervasive effects on the dynamic evolution of the US economy. Using an estimated structural dynamic factor model we find that more globally integrated markets exhibit significantly more pronounced responses than other measures of real economic activity. Impulse responses reveal a small but statistically significant ‘flight‐to‐safety’ effect, depressing government bond yields across the entire term structure following a shock to PU. Forecast error variance decompositions are predominantly composed of supply, demand, and PU shocks over all horizons, with PU shocks contributing less and supply shocks contributing more to forecast errors at longer horizons. Technology shocks, by contrast, are found to affect forecast accuracy closer to impact with quickly decaying contributions over extended forecast horizons. Copyright © 2015 John Wiley & Sons, Ltd.     

THE DEMAND FOR GASOLINE: EVIDENCE FROM HOUSEHOLD SURVEY DATA

In this paper we investigate the demand for gasoline in Canada using recent annual expenditure data from the Canadian Survey of Household Spending, over a 13‐year period from 1997 to 2009, on three expenditure categories in the transportation sector: gasoline, local transportation, and intercity transportation. In doing so, we use three of the most widely used locally flexible functional forms, the Almost Ideal Demand System (AIDS) of Deaton and Muellbauer (1980), the quadratic AIDS (QUAIDS) of Banks et al. (1997)—an extension of the simple AIDS model that can generate quadratic Engel curves—and the Minflex Laurent model of Barnett (1983), which can also generate quadratic Engel curves. We pay explicit attention to economic regularity, argue that unless regularity is attained by luck, flexible functional forms should always be estimated subject to regularity as suggested by Barnett (2002), and impose local curvature to produce inference consistent with neoclassical microeconomic theory. Our findings indicate that the curvature‐constrained Minflex Laurent model is the only model that is able to provide theoretically consistent estimates of the Canadian demand for gasoline. Our estimates show that the own‐price elasticity for gasoline demand in Canada is between ? 0.738 and ? 0.570 —less elastic than previously reported in the literature. Copyright © 2013 John Wiley & Sons, Ltd.     

The Effect of Import Competition on Firm Productivity and Innovation: Does the Distance to Technology Frontier Matter?

How does foreign competition affect growth and innovation in China? Using our unique measures of proximity of Chinese firms and industries to the world technology frontier, we find that despite vast sectoral heterogeneity, Chinese manufacturing industries have undergone rapid technological upgrading over the period of 2000–06. The distance to the world production frontier of firms and industries plays an important role in shaping the nexus between the competition pressure from foreign imports and domestic firms' growth and innovation behaviour. Our results support the theoretical predictions of Aghion et al. (2005, The Quarterly Journal of Economics, pp. 701–728) that import competition stimulates the domestic firms' productivity growth and R&D expenditure if firms and their industries are close to the world frontier, but discourages such incentives for laggard firms and industries. The two forces highlighted by the model operate for imports under the ordinary‐trade regime, for collective and private firms, and for imports originated from high‐income countries. Our findings are robust after controlling the influence of foreign investment, the reverse causality of regressors and the short‐term business cycle fluctuations.     

Regression Models with Variables of Different Frequencies: The Case of a Fixed Frequency Ratio*

An increasing variety of data frequencies available in economics, finance, etc. gives rise to a question how to build and estimate a regression model with variables observed at different frequencies. In a unifying framework of (m,d)‐aggregation we consider various approaches by discussing some potential and limitations. A Monte Carlo experiment and an empirical example illustrate that the traditional fixed aggregation approach, widely used in applied economics, might be inconsistent with data and highly inferior in terms of model precision.     

Dose–response modelling for bivariate covariates with and without a spike at zero: theory and application to binary outcomes

In epidemiology and clinical research, there is often a proportion of unexposed individuals resulting in zero values of exposure, meaning that some individuals are not exposed and those exposed have some continuous distribution. Examples are smoking or alcohol consumption. We will call these variables with a spike at zero (SAZ). In this paper, we performed a systematic investigation on how to model covariates with a SAZ and derived theoretical odds ratio functions for selected bivariate distributions. We consider the bivariate normal and bivariate log normal distribution with a SAZ. Both confounding and effect modification can be elegantly described by formalizing the covariance matrix given the binary outcome variable Y. To model the effect of these variables, we use a procedure based on fractional polynomials first introduced by Royston and Altman (1994, Applied Statistics 43: 429–467) and modified for the SAZ situation (Royston and Sauerbrei, 2008, Multivariable model‐building: a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables, Wiley; Becher et al., 2012, Biometrical Journal 54: 686–700). We aim to contribute to theory, practical procedures and application in epidemiology and clinical research to derive multivariable models for variables with a SAZ. As an example, we use data from a case–control study on lung cancer.     

Aggregation is not the solution: the PPP puzzle strikes back

Recently, Imbs, Mumtaz, Ravn and Rey (2005, hereinafter IMRR) have argued that much of the purchasing power parity (PPP) puzzle is due to upwardly biased estimates of persistence. According to them, the source of the bias is the existence of heterogeneous price adjustment dynamics at the sectoral level that established time series or panel data methods fail to control for. This paper re‐examines this claim in two steps. Firstly, we demonstrate that IMRR's measures of sectoral persistence are systematically downwardly biased because they are based on an inaccurate definition of the ‘average’ impulse response function (IRF). We then show that standard estimates of shock persistence are recovered after this bias is corrected. Secondly, building on the results in Mayoral (2008), which prove that aggregate and micro models induce the same shock persistence behavior, we show that estimates based on aggregate and sectoral exchange rates are, in fact, highly consistent. Thus, aggregation is not the solution to the PPP puzzle. Copyright © 2009 John Wiley & Sons, Ltd.     

Extending Institutional Analysis through Theoretical Triangulation: Regulation and Activity-Based Costing in Portuguese Telecommunications

Abstract

This paper examines why a Portuguese telecommunications company – Marconi – adopted activity-based costing (ABC). The focus lies in new institutional sociology (NIS), particularly the institutional change model of Dillard et al. (Accounting, Auditing and Accountability Journal, 17(4), pp. 506–542, 2004), supplemented by theoretical triangulation involving economic, labour process and actor network theories to enrich observations and extend theory. Why Marconi adopted ABC lay in a complex, interrelated chain of institutions, including the parent company, management consultants, national and European Union regulators, financial markets and consumer associations during market liberalization. ABC was a means and symbol of improved competitiveness and efficiency but its diffusion and adoption also involved mimetic, coercive and normative factors. In regulated environments external legitimacy and efficiency were intertwined and demonstrating efficiency using accounting symbols is problematic. The results confirm criticisms of early NIS research for dichotomizing economic and institutional pressures, assuming private organizations are exempt from institutional pressures and neglecting internal organizational dynamics. The Dillard et al. model accommodated many features of institutionalization but needed extension to incorporate the public interest, the role of boundary spanners across social levels and how intra-organizational factors and properties of the technology derived following translation and praxis play a part.     

Hidden group patterns in democracy developments: Bayesian inference for grouped heterogeneity

We propose a nonparametric Bayesian approach to estimate time‐varying grouped patterns of heterogeneity in linear panel data models. Unlike the classical approach in Bonhomme and Manresa (Econometrica, 2015, 83, 1147–1184), our approach can accommodate selection of the optimal number of groups and model estimation jointly, and also be readily extended to quantify uncertainties in the estimated group structure. Our proposed approach performs well in Monte Carlo simulations. Using our approach, we successfully replicate the estimated relationship between income and democracy in Bonhomme and Manresa and the group characteristics when we use the same number of groups. Furthermore, we find that the optimal number of groups could depend on model specifications on heteroskedasticity and discuss ways to choose models in practice.     

Refining Stylized Facts from Factor Models of Inflation

Factor models of disaggregate inflation indices suggest that sectoral shocks generate the bulk of sectoral inflation variance, but no persistence. Aggregate shocks, by contrast, are the root of sectoral inflation persistence, but have negligible relative variance. We show that simple factor models do not cope well with essential features of price data. In particular, sectoral inflation series are subject to features such as measurement error, sales and item substitutions. In factor models, these blow up the variance of sector‐specific shocks, while reducing their persistence. We control for such effects by estimating a refined factor model and find that inflation variance is driven by both aggregate and sectoral shocks. Sectoral shocks, too, generate substantial inflation persistence. Both findings contrast with earlier evidence from factor models, but align well with recent micro evidence. Our results have implications for the foundations of price stickiness, and provide quantitative inputs for calibrating models with sectoral heterogeneity. Copyright © 2014 John Wiley & Sons, Ltd.     

NONSENSE REGRESSIONS BETWEEN INTEGRATED PROCESSES OF DIFFERENT ORDERS

Abstract Herein we develop an analytical study of the asymptotic distributions obtained when we run linear regressions in the levels of stochastically independent integrated time series when the orders of integration of the dependent and independent variables are different. These theoretical findings largely explain the Monte Carlo results recently reported in Banerjee et al. (1993).     

Sectoral Productivity,Density and Agglomeration in the Wider Europe

Abstract

We then test this model using panel data for five sectors on regional-level data for 27 EU Member States. Our results for the aggregate economy confirm previous estimates. For our full sample of countries the sectoral-level results also indicate significant agglomeration effects. Considering differences in the extent of agglomeration effects between new and old EU Member States, however, leads to the conclusion that agglomeration effects tend to be stronger at both the aggregate and the sectoral level for new Member States.

Productivité sectorielle, densité et agglomération dans l'Europe élargie

RÉSUMÉ?Nous testons ensuite ce modèle en utilisant des données de panel pour cinq secteurs à l'échelon régional dans 27 états membres de l'UE. Les résultats que nous obtenons pour l'économie dans son ensemble confirment les estimations précédent. Pour notre échantillon complet de pays, les résultats au niveau sectoriel font état d'importants effets d'agglomération. Si, toutefois, l'on tient compte des différences quant à l'étendue des effets d'agglomération entre nouveaux et anciens états membres de l'UE, on en conclut que les effets d'agglomération ont tendance à être plus prononcés à l'échelon global et à l'échelon sectoriel chez les nouveaux états membres.

Productividad sectoral, densidad y aglomeración en la Europa más amplia

RÉSUMÉN?A continuación, ensayamos este modelo utilizando datos de panel para cinco sectores aplicables a datos de nivel regional sobre 27 estados miembros de la UE. Nuestros resultados en relación con la economía agregada confirman las estimaciones anterior. Con respecto a nuestra muestra completa de países, los resultados de nivel sectoral también indican efectos significativos de la aglomeración. No obstante, la consideración de diferencias en la extensión de los efectos de la aglomeración entre nuevos y antiguos estados miembros de la UE, lleva a la conclusión de que los efectos de la aglomeración tienden a ser más pronunciados en los nuevos estados miembros, tanto a nivel agregado como sectoral.

     

Multiple equilibria in two-sector monetary economies: An interplay between preferences and the timing for money

In this paper, we study the occurrence of local indeterminacy in two-sector monetary economies. We consider a general MIUF model with two alternative timings in monetary payments: the Cash-In-Advance timing, in which the cash available to buy goods is money in the consumers’ hands after they leave the bond market but before they enter the goods market, and the Cash-After-the-Market timing, in which agents hold money for transactions after leaving the goods market. We consider three standard specifications of preferences: the additively separable formulation, the Greenwood–Hercovitz–Huffman (GHH) (Greenwood et al., 1988) formulation and the King–Plosser–Rebelo (KPR) (King et al., 1988) formulation. First, we show that for all the three types of preferences, local indeterminacy occurs under the CIA timing with a low enough interest rate elasticity of money demand. Second, we show that with the CAM timing, although determinacy always holds under separable preferences, local indeterminacy can occur with GHH and KPR preferences. We thus prove that compared to aggregate models, two-sector models provide new rooms for local indeterminacy when non-separable standard preferences are considered.     

Discussion

I thoroughly enjoyed reading the article by Bhadra et. al. (2020) and convey my congratulations to the authors for providing a comprehensive and coherent review of horseshoe-based regularization approaches for machine learning models. I am thankful to the editors for providing this opportunity to write a discussion on this useful article, which I expect will turn out to be a good guide in the future for statisticians and practitioners alike. It is quite amazing to see the rapid progress and the magnitude of work advancing the horseshoe regularization approach since the seminal paper by Carvalho et al. (2010). The current review article is a testimony for this. While I have been primarily working with continuous spike and slab priors for high-dimensional Bayesian modeling, I have been following the literature on horseshoe regularization with a keen interest. For my comments on this article, I will focus on some comparisons between these two approaches particularly in terms of model building and methodology and some computational considerations. I would like to first provide some comments on performing valid inference based on the horsheshoe prior framework.     

Mind the context gap: a critical review of engagement within the public sector and an agenda for future research

Abstract

In this review paper, we critically examine the evidence base relating to engagement within the public sector given a wide range of public services have faced acute human resource challenges over recent years. Our review of 188 empirical studies reveals that much of the evidence focuses attention on individual and job level factors, such that specific public sector contextual contingencies have rarely been considered. Through identifying significant ‘context gaps’, we present a future research agenda addressing the following key areas: i) clarifying the relationship between engagement and public service motivation, ii) further contextualizing general engagement models, iii) exploring cultural, socio-political, and institutional factors in more depth, iv) encouraging a more critical perspective on engagement, v) understanding the variation in the experience of engagement across different public services/delivery models, and vi) connecting more strongly with practical concerns and initiatives within public organizations. In presenting this agenda, we highlight how engagement and HRM scholars can more strongly embed their research within a sectoral context.     

Specification Sensitivity in Right‐Tailed Unit Root Testing for Explosive Behaviour

This article aims to provide some empirical guidelines for the practical implementation of right‐tailed unit root tests, focusing on the recursive right‐tailed ADF test of Phillips et al. (2011b). We analyze and compare the limit theory of the recursive test under different hypotheses and model specifications. The size and power properties of the test under various scenarios are examined and some recommendations for empirical practice are given. Some new results on the consistent estimation of localizing drift exponents are obtained, which are useful in assessing model specification. Empirical applications to stock markets illustrate these specification issues and reveal their practical importance in testing.     

A Pairwise Difference Estimator for Partially Linear Spatial Autoregressive Models

Abstract

We propose a pairwise difference estimator for partially linear spatial autoregressive models with heteroscedastic or/and spatially correlated error terms. In comparison with other competing estimators, e.g. the profile QMLE (Su & Jin, 2010) and the semiparametric GMM estimator (Su, 2012), our estimator has the advantage of computational simplicity particularly when one is interested in estimating the finite dimensional parameters in the model. Large sample properties of the estimator are formally established and a consistent estimate of the asymptotic CV matrix is provided. We then use the method to robustly estimate the effect of strategic interaction in deciding local school spending.

RÉSUMÉ nous proposons un estimateur de différence par paire pour des modèles autorégressifs spatiaux partiellement linéaires, avec conditions d'erreurs à corrélation hétéroscédastique et/ou spatiale. Par rapport à d'autres estimateurs possibles, p.ex. le QMLE de profil (Su & Jin, 2010), et l'estimateur GMM semi-paramétrique (Su, 2012), notre estimateur présente l'avantage de la simplicité du calcul, notamment lorsque l'on s'intéresse à l'estimation des paramètres dimensionnels finis dans le modèle. Les propriétés de grand échantillon de l'estimateur sont établies officiellement, et une estimation homogène de la matrice CV asymptotique est fournie. Nous utilisons ensuite la méthode d'estimation consistante de l'effet de l'interaction stratégique dans les décisions sur les dépenses des écoles locales.

EXTRACTO Proponemos un estimador de diferencias por pares para modelos autorregresivos espaciales parcialmente lineales con términos de error heteroscedásticos o/y espacialmente correlacionados. En comparación con otros estimadores competidores, p. ej., QMLE (Su & Jin, 2010) y el estimador GMM semiparamétrico (Su, 2012), nuestro estimador tiene la ventaja de la simplicidad computacional, particularmente cuando uno está interesado en estimar los parámetros dimensionales finitos en el modelo. Las propiedades de muestras grandes del estimador se establecen formalmente y se proporciona una estimación constante de la matriz CV asimptótica. Seguidamente, utilizamos el método para estimar contundentemente el efecto de la interacción estratégica para decidir el gasto de escuelas locales.

摘要 : 我们对部分线性空间自回归模型提出了–种成对差异估计量, 采用异方差或/和空间相关误差项。与其他估计量, 例如包络准最大似然估计 (Su & Jin, 2010) 和半参量 GMM 估计 (Su, 2012) 相比, 我们的估计量具有计算复杂度低的优势, 尤其是用于估计模型中的有限维度参数时。我们已经建立了这种估计方法的大采样样本, 还提供对渐近线 CV 矩阵的–致估计。接着, 使用这种方法, 我们透彻分析了政策对本地学校支出的影响。     

Replication of Grier,Henry, Olekalns and Shields (2004): the Asymmetric Effects of Uncertainty on Inflation and Output Growth

In their influential work Grier et al.(The asymmetric effects of uncertainty on inflation and output growth. Journal of Applied Econometrics 2004; 19 : 551–565) examine the effects of growth and inflation uncertainties on their average rates. The current study replicates their main results and performs a similar analysis on a more recent dataset. Their findings are confirmed to a large extent. Copyright © 2015 John Wiley & Sons, Ltd.