Empirical Economics

The idea of transferability is to employ in model estimation, fitted model parameters computed from a different data set. The combined estimator approach to the transferability problem is expressed as a linear combination of the unbiased direct estimators on the two data sets. The major gain is in variance reduction. The combined estimator is shown to have superior accuracy, in a Mean Square Error sense, to a unbiased direct estimator whenever the transfer bias is relatively small. A test that indicates if the combined estimator is superior to the direct estimator is provided. Variances of the direct estimators are assumed to be known. Monte Carlo experiments are performed to assess the quality of the approximations. The results show that the approximations used are highly conservative. An empirical example of the combined estimator applied to a discrete choice problem is presented.

The aim of this work is to analyze the influence of the spatial effects in the evolution of the regional employment, thus improving the explanation of the existing differences. With this aim, two non-parametric techniques are proposed: spatial shift-share analysis and spatial filtering.

In order to restore the global economy to solid and sustainable growth, capitalism needs to be reformed from an irrational profit-maximising model into a more rational profit-equalising one. In the aggregate the growth rate of gross operating surplus plus gross mixed income must equal that of gross domestic product and not exceed it, thereby ensuring that the compensation of employees increases proportionally as well. This would prevent the deflationary effect of having continually to refinance debt as it increases disproportionally relative to GDP over successive economic cycles, the root cause of which is not treating the compensation of employees as both a cost and an income in the pursuit of maximising profitability. In SNA national income accounting methodology, income derived GDP is equal to gross operating surplus plus gross mixed income plus compensation of employees plus taxes on production and imports less subsidies. Thus, as profit and mixed income increase relative to GDP, employee compensation must necessarily decrease proportionally with allowances for taxes and subsidies. As wages and salaries are both a cost and an income, which is a self-evident truth, if they are suppressed as a cost on the supply side of an economy in order to maximise profit, this reduction affects aggregate demand by a proportional amount on the demand side by weakening the multiplier. This distorts supply and demand, leading to serious economic imbalances over time. Prices or rather their relative components of wages and profit determine the equilibrium of supply and demand in the aggregate rather than the other way around as the fundamental tenet of neo-classical economics proposes.

The equation below provides evidence that the first principle of wages being a cost and an income is key to balancing supply and demand, and income and expenditure over the economic cycle as well as economics becoming a fully-fledged science. Using United States’ national accounts time series data between 1972 and 2007 to empirically demonstrate a causal connection between the real and financial economies, the increasing dysfunction of the business cycle can be explained. Evidence from other national economies is examined as well. Despite wages being both a cost and a source of demand being obvious and fundamental to Keynes’ demand side theory in his General Theory, it has never been properly acknowledged or its effects fully understood. This reluctance to examine profit is an example of the dialectical opposition between convention based on excessive self-interest in the face of a seemingly uncertain and threatening environment and reason based on the underlying scientific laws of nature. Convention is always stronger than reason in the short to medium term and is only forced to become more rational in the longer term once it has finally collapsed under the weight of its contradiction with reality. The convention of profit-maximising capitalism could soon be at this point if the wall of corporate refinancing it faces in the next few years proves to be insurmountable.

A small macroeconomic model is constructed starting from a German money demand relation for M3 based on quarterly, seasonally unadjusted data for the period from 1976 to 1996. In contrast to previous studies we build a vector error correction model for M3, GNP, an inflation rate and an interest rate spread variable to represent opportunity costs of holding money. Furthermore, import price inflation is added as an exogenous variable. The model is used to analyze the relation between money growth and inflation by means of an impulse response analysis.

En este artículo se presenta evidencia en relación al número de tendencias comunes estocásticas existentes en tres monedas representativas del ERM. Los resultados obtenidos indican la presencia de una única tendencia común para dichos tipos de cambio. Dicha tendencia común puede ser interpretada como los fundamentos no paramétricos de dichas monedas dentro del ERM, lo cual indica que en un sistema cambiario como el Sistema Monetario Europeo los tipos de cambio tienen que ser modelizados de forma conjunta. Usando una técnica no paramétrica, el algoritmo ACE (Expectativas Condicionales Alternativas), obtenemos evidencia de la existencia de no-linealidades para dos de las tres monedas analizadas, con una forma funcional, relativa a los fundamentos no paramétricos estimados, similar a la forma en S que se obtiene a partir del modelo básico de zonas objetivo.

This paper proposes an empirical model for the modi®ed pecking order theory (MPO) in which both trade-o¨(TO) and pecking order (PO) models are nested. The MPO model is speci®ed as an error-correction mechanism and applied to a vast panel data-set. Unlike previously estimated ®nancial models, it avoids a number of problems: the mis-speci®cation of dynamics, the approximation of the target leverage using the historical mean, the constrained estimation of the free cash¯ow components in a unique parameter. The MPO model is particularly good at explaining``hybrid'' systems (neither marketbased nor bank-based) such as the Italian one, in which companies are a mixture of two types: TO-type ®rms with a long-term optimal debt ratio towards which they converge; PO-type ®rms for whom the short-term availability of internal funds for investment may interfere with the process of adjustment towards the target leverage. Finally, the MPO model enables us to separately test the individual relevance of each of the restricted (``pure'') TO and PO models: results con®rm their mis-speci®cation and clearly point towards the excellent empirical performance of the MPO model.

Using a simulation design that is based on empirical data, a recent study by Huber, finds that distance-weighted radius matching with bias adjustment as proposed in is competitive among a broad range of propensity score-based estimators used to correct for mean differences due to observable covariates. In this paper, we further investigate the finite sample behaviour of radius matching with respect to various tuning parameters. The results are intended to help the practitioner to choose suitable values of these parameters when using this method, which has been implemented in the software packages GAUSS, STATA and R.

Out-of-sample employment forecasts for 33 U.S. industries which are likely to be sensitive to the federal minimum wage are, more often than not, more accurate when information about the minimum wage is not taken into account. This is true even in instances where this information improves wage forecasts. When employment forecasts conditional on the minimum wage are better, the improvement is typically small. These results are invariant to the number of workers previously making less than the new minimum wage, and to the value of the minimum wage relative to industry average wages.

This article tests whether health has improved income or income has improved health in OECD countries over the last 50 years. A theoretical framework for both directions of causation is first outlined. A panel time-series approach is then taken and, unlike similar work, common shocks across countries ('cross-sectional dependence') are taken into account in the analysis using the PANIC (Panel Analysis of Non-stationarity in Idiosyncratic and Common components) approach of Bai and Ng. It is found that better health improves income more generally while income in turn also affects health. This finding is shown to be robust to dynamic specification.

Several studies have developed empirical models of U.K. money demand using the century of annual and phase-average data in . The current paper evaluates key models from those studies, employing tests of constancy and encompassing. The evidence strongly favors an annual model from , whereas models based on the phase-average data fare poorly.

Between June 1998 and March 2006, the price index of apartment houses in Seoul, Korea, more than doubled, while fundamentals such as GDP, wage, and population increased by less than 35%. This study examines the role of a rational speculative bubble in this price surge. We find that unobservable information explains part of the price volatility; and that a rational bubble proxy is a significant driver of prices. However, neither latent information nor rational bubble is enough to explain the recent housing price appreciation, even in conjunction with observable fundamentals.

This paper investigates the properties of Dickey-Fuller tests for seasonally unadjusted quarterly data when deterministic seasonality is present but it is neglected in the test regression. While for the random walk case the answer is straightforward, an extensive Monte Carlo study has to be performed for more realistic processes and testing strategies. The most important conclusion is that the common perception that deterministic seasonality has nothing to do with testing for the long-run properties of the data is incorrect. Further numerical evidence on the shortcomings of the general-to-specific t-sig lag selection method is also presented.

A quadratic Box-Cox methodology is presented for choice of flexible functional form that includes consistent computation of variance estimates. Empirical viability of the procedure is investigated by specifying a dual profit function using highly aggregated U.S. agricultural data. Conditional and unconditional variance estimates for the parameters are compared and contrasted. Like-lihood ratio tests are utilized to discriminate among the generalized Leontief, normalized quadratic, translog, and square-rooted quadratic functional forms. Statistical results indicate that the squarerooted quadratic is the preferred choice of functional form for these data, followed by the normalized quadratic.

The contribution of different types of public infrastructure on private production is investigated using time-series of cross-section data for the 48 contiguous states over the period [1970][1971][1972][1973][1974][1975][1976][1977][1978][1979][1980][1981][1982][1983][1984][1985][1986]. A Cobb-Douglas production function is estimated with unobserved state-specific effects. Measurement errors in public capital stock and its components are detected and rectified.

This paper serves as a partial introduction to and survey of the literature on Markov-switching models. We review the history of this class of models, describe their mathematical structure, and exposit the basic ideas behind estimation and inference. The paper also describes how the approach can be extended in a variety of directions, such as non-Gaussian distributions, time-varying transition probabilities, vector processes, state-space and GARCH models, and surveys recent methodological advances. The contributions of the other papers in this volume are reviewed. A final section o¤ers conclusions and implications for policy.

This paper employs the recently developed structural stability test with multiple regime shifts and grid bootstrapping methods to model US inflation dynamics over the past half century. Our empirical results suggest that the persistence of inflation has witnessed significant declines over the most recent period of low inflation and this helps to embed a low inflation environment. The finding is

In this paper we develop a dynamic model for integer counts to capture fundamental properties of financial prices at the transaction level. Our model relies on an autoregressive multinomial component for the direction of the price change and a dynamic count data component for the size of the price changes. Since the model is capable of capturing a wide range of discrete price movements it is particularly suited for financial markets where the trading intensity is moderate or low. We present the model at work by applying it to transaction data of two shares traded at the NYSE traded over a period of one trading month. We show that the model is well suited to test some theoretical implications of the market microstructure theory on the relationship between price movements and other marks of the trading process. Based on density forecast methods modified for the case of discrete random variables we show that our model is capable to explain large parts of the observed distribution of pr...

The performances of alternative two-stage estimators for the endogenous switching regression model with discrete dependent variables are compared, with regard to their usefulness as starting values for maximum likelihood estimation. This is especially important in the presence of large correlation coe½cients, in which case maximum likelihood procedures have di½culties to converge. Monte-Carlo simulations indicate that an estimator that corrects for conditional heteroskedasticity of the residuals is superior in almost all instances, and especially when maximum likelihood is problematic. This result is also obtained in an empirical example in which o¨-farm work participation equations of farm women are conditional on farm work participation status.

In this paper, we compare alternative estimation approaches for factor augmented panel data models. Our focus lies on panel data sets where the number of panel groups (N) is large relative to the number of time periods (T). The principal component (PC) and common correlated effects (CCE) estimators were originally developed for panel data with large N and T, whereas the GMM approaches of Ahn et al. (J Econ 728 174:1–14, 2013) and Robertson and Sarafidis (J Econ 185(2):526–541, 2015) assume that T is small (that is T is fixed in the asymptotic analysis). Our comparison of existing methods addresses three different issues. First, we analyze the possibility of an inappropriate normalization of the factor space (the so-called normalization failure). In particular we propose a variant of the CCE estimator that avoids the normalization failure by adapting a weighting scheme inspired by the analysis of Mundlak (Econometrica 46(1):69–85, 1978). Second, we analyze the effects of estimating v...

The current literature on Information and Communication Technology (ICT) and planning suggests that the use of Information Technology (IT) in local government can enhance the management and functioning of cities. Of particular interest is the phenomenon of e-government, where debates and information surrounding local government matters are conducted in cyberspace. Of relevance also, are the networking opportunities that the Internet can facilitate between city governments and the institutional learning that can emanate from that. The increasing use of web-based Geographic Information Systems (GIS) applications raises awareness of spatial issues that impact on defined municipal areas, whilst interactive mapping provides opportunities for addressing spatial concerns virtually. Most of the literature does, however, focus on the experience of developed countries where capacity and resources permit a sophisticated understanding of ICT. Yet, evidence suggests that these tools are also used in some developing countries, with India often cited as one of the leading countries in achieving ICT prominence, but little seems to be published about this experience in Southern Africa. There are a number of innovative initiatives underway in South African local governments but most of these interventions are in their infancy. In contrast, there are a number of examples in developed countries that may provide some guidance for developing cities. This paper examines the Smart City initiative in Brisbane in Australia, and compares it with moves currently underway in Durban, South Africa to incorporate ICT in local governance. The intention is to expose the differences in approach, understand the capacity and resource issues that may impact, and draw some conclusions with regards to future interventions in Durban. Overall, the paper provides an initial conceptual landscape that begins to determine the extent to which ICT in local government can provide opportunities for Durban by learning from the experience of Brisbane, Australia.

Analyzing equity market co-movements is important for risk diversification of an international portfolio. Copulas have several advantages compared to the linear correlation measure in modeling co-movement. This paper introduces a copula ARMA-GARCH model for analyzing the co-movement of international equity markets. The model is implemented with an ARMA-GARCH model for the marginal distributions and a copula for the joint distribution. After goodness of fit testing, we find that the Student's t copula ARMA(1,1)-GARCH(1,1) model with fractional Gaussian noise is superior to alternative models investigated in our study where we model the simultaneous co-movement of nine international equity market indexes. This model is also suitable for capturing the long-range dependence and tail dependence observed in international equity markets.

We analyze the dynamic relationship between public investment and output. Whereas existing empirical studies on the e¨ects of public capital typically rely on single-equation models of the private sector, we investigate the role of public investment in an economy by examining impulse responses derived from vector autoregressions. Using data from six industrial countries, we speci®cally examine the following questions: does higher public investment lead to GDP increases; is there reverse causation from output to public investment; and what are the e¨ects of expenditure-neutral budget shifts from public consumption to public investment.

Mediation analysis aims at evaluating the causal mechanisms through which a treatment or intervention affects an outcome of interest. The goal is to  disentangle the total treatment effect into an indirect effect operating through one or several observed intermediate variables, the so-called mediators, as well as a direct effect reflecting any impact not captured by the observed mediator(s). This paper reviews methodological advancements with a particular focus on applications in economics. It defines the parameters of interest, covers various identification strategies, e.g. based on control variables or instruments, and presents sensitivity checks. Furthermore, it discusses several extensions of the standard mediation framework, such as multivalued treatments, mismeasured mediators, and outcome attrition.

Limited data means that prior structure is needed when working with large demand systems. The cost function is a convenient vehicle for generating demand systems incorporating such structure. While the cost function directly yields Hicksian demand functions they will not usually have an explicit representation as Marshallian demand equations i.e. in terms of the observable variables. With fast hardware and modern software, however, this need not hinder the estimation of the (implied) Marshallian demand equations. This paper develops the formal theory for using cost functions in this context, and reports on initial trials on the operational feasibility of the method.

This article provides estimates of price-marginal cost ratios or mark-ups for 50 sectors in eight Euro area countries and the US over the period 1981-2004. The estimates are obtained applying the methodology developed by Roger (J Polit Econ 103:316-330, 1995) on the EU KLEMS March 2007 database. Five stylized facts are derived.

In recent years more and more numerous are the rankings published in the newspapers or technical reports available, covering many aspects of higher education, but in many cases with very conflicting results between them, due to the fact that universities’ performances depend on the set of variables considered and on the methods of analysis employed. The aim of this study is to rank higher education institutions (HEIs) in Italy, comparing parametric and non-parametric approaches: we firstly apply a so-called double bootstrap Data Envelopment Analysis (DEA) to generate unbiased coefficients (Simar and Wilson, 2007) and then a Stochastic Frontier Analysis (SFA), modelling the production set through an output distance function, applying  a within transformation to data as developed  by Wang  and  Ho  (2010), to evaluate which determinants have an impact on universities’ efficiencies. The findings reveal that, on average and among the macro-areas of the country, the level of efficiency does not change significantly among estimation methods which, instead, generate different rankings. This may guide universities’ managers and policymakers as rankings have a strong impact on academic decision-making and behaviour, on the structure of the institutions and also on students and graduates recruiters. Variables describing institution, market place and environment have an important role in explaining (in)efficiency.

El proceso de elegir, es desde aquellos textos de Adam Smith, una cuestión recurrente en el transcurso del pensamiento económico. Además, y con mayor énfasis en los últimos años, el modo en que los individuos seleccionan sus preferencias ha sido también un tema a tratar en vastas áreas de las ciencias humanas: psicología, sociología, antropología. Es bien sabido que los objetos de las preferencias y las elecciones pueden ser diferentes y diferente también el modo de optar por ellos. En la teoría de la elección del consumidor, primera aproximación académica al tema desde la economía (más tarde vendría la opción en las teorías de las finanzas públicas), son canastas de bienes y servicios. Como las preferencias de bienes individuales dependen de que otros bienes uno dispone, los objetos de preferencias deberían, en general y según la opinión de Hausman, ser tomados como descripciones completas de estados del mundo . En el razonamiento de los economistas, además, se postula el supuesto de racionalidad (con sus variantes) para el proceso de los agentes. Ahora bien, la combinación entre elección y racionalidad, en el caso de la teoría del consumidor, está ligada a la utilización instrumental de la utilidad ordinal como hilo conductor conceptual. En el momento en que teóricamente se plantean dudas epistemológicas acerca de la pertinencia real de la utilidad ordinal en el proceso, la verificación de la utilidad cardinal presente en los individuos se torna imprescindible. En el presente paper, se realizará a cabo un experimento enmarcado en las teorías de la preferencia revelada (Harbought at al) usando como sujetos del experimento a personas de diferente sexo, edad y conocimiento de economía. El objetivo, en la primera parte del mismo, será encontrar violaciones al axioma débil de la preferencia revelada, buscando contradicciones empíricas al interior mismo de la teorización sobre las elecciones. En segundo lugar, se buscará contrastar la elección absoluta, presente en la utilidad cardinal, con la utilidad instrumental en la cual la economía descansa.

We analyze the nature of persistence in macroeconomic fluctuations. The current view is that shocks to macroeconomic variables (in particular real GNP) have effects that endure over an indefinite horizon. This conclusion is drawn from the presence of a unit root in the univariate time series representation. Following Perron (1989), we challenge this assessment arguing that most macroeconomic variables are better construed as stationary fluctuations around a breaking trend function. The trend function is linear in time except for a sudden change in its intercept in 1929 (The Great Crash) and a change in slope after 1973 (following the oil price shock). Using a measure of persistence suggested by Cochrane (1988) we find that shocks have small permanent effects, if any, To analyze the effects of shocks at finite horizon, we select a member of the ARMA(p, q) class applied to the appropriately detrended series. For the majority of the variables analyzed the implied weights of the moving-average representation have the once familiar humped shape.

In a panel data model with random effects, when autocorrelation in the error is considered, (Gaussian) maximum likelihood estimation produces a dramatically large number of corner solutions: the variance of the random effect appears (incorrectly) to be zero, and a larger autocorrelation is (incorrectly) assigned to the idiosyncratic component. Thus heterogeneity could (incorrectly) be lost in applications to panel data with customarily available time dimension, even in a correctly specified model. The problem occurs in linear as well as nonlinear models. This paper aims at pointing out how serious this problem can be (largely neglected by the panel data literature). A set of Monte Carlo experiments is conducted to highlight its relevance, and we explain this unpleasant effect showing that, along a direction, the expected log-likelihood is nearly flat. We also provide two examples of applications with corner solutions.

This paper studies the empirical link between international tourism and trade. We apply dynamic heterogeneous panel data techniques to analyse both long-term and short-term relationship for the case study of OECD countries. This link is studied by estimating the cointegration vector and analysing the short and long-run causality between variables. The analysis recognises that inbound tourism can promote international trade and also that international flow of goods requires and may encourage tourist arrivals and departures. The statistical significance of this relationship supports the presence of business opportunities due to the potential complementary relationship between tourism and trade. The results suggest a short-run relationship between tourism and trade, and that these variables are cointegrated.

The present paper discusses the stochastic stationarity of New Zealand exchange rates in light of new time series methods and new tests. The question of whether the real exchange rates have a unit root or are mean reverting is set in the general framework of fractionally integrated models. The estimates sustain the claim that New Zealand real exchange series are not stationary. However, it is shown that nonstationarity is compatible with parity reversion in the framework of fractional unit-root models.

The emergence of Information and Communication Technologies (ICTs), in particular the Internet, has generated new enthusiasms about the development prospects for poor economies. Many now think that new technologies can provide a faster route to better livelihoods and improved quality of life than the one afforded by the standard process of industrialization. The opposing view holds that the focus on ICTs will detract attention from the more fundamental task of addressing the basic problems of economic development.

In this paper we show how the potential misspeci®cation of the consumption function can be ameliorated by approximating any unmodelled long run variation with an unobserved component in the form of a timevarying trend. This methodology is applied to Greek, Portuguese and Spanish consumption functions during the post-second World war period. The empirical evidence suggests that there are many determinants of long-run consumption in these countries, in addition to income and in¯ation, and these unobserved long-run e¨ects are captured by a nonstationary stochastic component. The long-run elasticity of consumption with regards to the unobserved component is greater than unity in all countries.

This paper applies data envelopment analysis (DEA) to assess the efficiency, technical and scale, of both departments and faculties at University of Salerno in the South of Italy. Particular attention has been paid on two main activities, teaching and research, and on two large groups, science and technology (ST) sector and humanity and social science (HSS) sector. The findings, based on data from 2005 to 2009, suggest that the ST sector is more efficient in terms of quality of research than the HSS sector that instead achieves higher efficiency in teaching activities. The efficiency estimates strongly depend on the output specification, given that the use of several quality proxies as output reduces the performance and its differentials for both research and teaching activities. The Malmquist index is calculated to measure changes in productivity. A bootstrap technique is also used to provide confidence intervals for efficiency scores and to determine accurate performance estimates.

This paper investigates the long-run relationship between labour productivity and employment, and between labour productivity and real wages in the case of the Indian manufacturing sector. The panel data set consists of 17 two-digit manufacturing industries for the period 1973-74 to 1999-2001. We find that productivity-wages and productivity-employment are panel cointegrated for all industries. We find that both employment and real wages exert a positive effect on labour productivity. We argue that flexible labor market has a significant influence on manufacturing productivity, employment and real wages in case of Indian manufacturing. JEL Codes: O47, O30, O53

This paper tests for unit roots, cointegration, and Granger-causality in the exports-GDP nexus in Canada 1947–96, using both bivariate and trivariate models. Contrary to previous studies we cannot conclude that economic growth is either export-led, or output-driven, but rather that strong bi-directional causality exists between Canadian exports and GDP, and the GDP of its main trading partner, the United States.

This note discusses some issues that arise when framework is used to analyze cointegrating relationships among variables with deterministic linear time trends. We distinguish "stochastic" and "deterministic" cointegration, arguing that stochastic cointegration is sufficient for the existence of an error correction representation and that it is often the hypothesis of interest in empirical applications. We show that Johansen's (1991) method, which includes only a constant term in the estimated regression system, does not allow for stochastic cointegration. We propose to modify Johansen's method by including a vector of deterministic linear trends in the estimated model. We present tabulated critical values of the maximal eigenvalue and trace statistics appropriate for this case. We discuss the circumstances under which our modification may be useful.

 The Poverty function is investigated in Laos.  The Ordinary Least Squares (OLS) approach is applied.  Road infrastructure affects poverty. Abstract Purpose: Road access is important for connecting rural production to urban markets to ensure income generation, to help improve living standards and reduce poverty. Laos is a land-locked country with poor road networks. Methodology: The OLS method is applied. In addition, about thirty percent of the population is under the poverty line. Findings: Research findings indicate road access during all seasons has a positive significant impact on poverty reduction, by increasing the real expenditure per capita level. We found that road access in all seasons allow farmers year-round access to the urban market, to expand agricultural production to improve productivity and finally to help reduce poverty, especially in rural areas of Lao PDR. Our study also supports previous studies and the Lao government's policies in its Seventh Five-Year Socio-Economic Development Plan for increasing investment in infrastructure.

There is a wide literature on the dynamic adjustment of employment and its relationship with the business cycle. Our aim is to propose a statistical model that offers a congruent representation of post-war UK labour market. We use a cointegrated vector autoregressive Markov-switching model where some parameters change according to the phase of the business cycle. Output, employment, labour supply and real earnings are found to have a common cyclical component. The long run dynamics are characterized by two cointegrating vectors: trend-adjusted labour productivity and the labour share. Despite there having been many changes affecting this sector of the UK economy, the Markov-switching vector-equilibrium-correction model with three regimes representing recession, growth and high growth provides a good characterization of the sample data over the period 1966(3)-1993(1) In an out-of-sample forecast experiment over the period 1991(2)-1993(1) it beats linear and non-linear model alternatives. The results of an impulse-response analysis highlight the dangers of using VARs when the constancy of the estimated coefficients has not been established.

This paper proposes a new approach to jointly model the trading process and the revisions of market quotes. This method accommodates asymmetries in the dynamics of ask and bid quotes after trade related shocks. The empirical spec ification is a vector error correction (VEC) model for ask and bid quotes, with the spread as the co integrating vector, and with an endogenous trading process. This model extends the vector autoregressive (VAR) model introduced by Hasbrouck (Hasbrouck J (1991) Measuring the information content of stock trades. J Finance 46:179 207). We provide evidence against several symmetry assumptions, very familiar among microstructure models. We report asymmetric adjustments of ask and bid prices to trade related shocks, and asymmetric impacts of buyer and seller initiated trades. In general, buys are more informative than sells. The likelihood of symmetric quote responses increases with volatility. We show that our findings are robust across different model specifications, time frequencies, and trading periods. Moreover, we find similar asymmetries in markets with different microstructures.

Abstract. Many researchers use GARCH models to generate volatility fore-casts. Using data on three major US dollar exchange rates we show that such forecasts are too high in volatile periods. We argue that this is due to the high persistence of shocks in GARCH forecasts. ...

A common finding in the empirical literature on the validity of purchasing power parity (PPP) is that it holds when tested for in panel data, but not in univariate (i.e. country-specific) analysis. The usual explanation for this mismatch is that panel tests for unit roots are more powerful than their univariate counterparts. In this paper we suggest an alternative explanation. Existing panel methods assume that cross-unit cointegrating relationships, that would tie the units of the panel together, are not present. Using simulations, we show that if this important underlying assumption of panel unit root tests is violated, the empirical size of the tests is substantially higher than the nominal level, and the null hypothesis of a unit root is rejected too often even when it is true. More generally, this finding warns against the ''automatic'' use of panel methods for testing for unit roots in macroeconomic time series.