CONDITIONAL DURATION MODELS FOR HIGH‐FREQUENCY DATA: A REVIEW ON RECENT DEVELOPMENTS

This paper reviews the recent literature on conditional duration modeling in high‐frequency finance. These conditional duration models are associated with the time interval between trades, price, and volume changes of stocks, traded in a financial market. An earlier review by Pacurar provides an exhaustive survey of the first and some of the second generation conditional duration models. We consider almost all of the third‐generation and some of the second‐generation conditional duration models. Notable applications of these models and related empirical studies are discussed. The paper may be seen as an extension to Pacurar.     

PURCHASING POWER PARITY FOR DEVELOPING AND DEVELOPED COUNTRIES. WHAT CAN WE LEARN FROM NON‐STATIONARY PANEL DATA MODELS?

Abstract.  The aim of this paper is to apply recently developed panel cointegration techniques proposed by Pedroni ( Oxford Bulletin of Economics and Statistics 61 (1999): Supplement, 653–670; Econometric Theory 20 (2004): 597–625) and generalized by Banerjee and Carrion-i-Silvestre (Working Paper 591, European Central Bank, February 2006) to examine the robustness of the PPP concept for a sample of 80 developed and developing countries. We find that strong PPP is verified for OECD countries and weak PPP for Middle East and North African countries. However, in African, Asian, Latin American and Central and Eastern European countries, PPP does not seem relevant to characterize the long-run behavior of the real exchange rate. Further investigations indicate that the nature of the exchange rate regime does not condition the validity of PPP, which is more easily accepted in countries with high rather than low inflation.     

SPLIT–PLOT DESIGN: MODEL AND ANALYSIS FOR COUNT DATA

The analysis of count response data from designed experiments is well–known for independent response variables having the Poisson distribution. For experimental designs where responses are dependent, no general results seem to be available. An example of this type of design is the split–plot design, where sub–plot responses are essentially dependent within whole plots.
In this paper, a model will be proposed for split–plot count data and a separate analysis for whole plot and sub–plot data will be presented. It is interesting to note, that the same model is used in the quite different context of consumer buying behaviour. It is derived by Goodhardt, Ehrenberg and Chatfield and it was called the 'Dirichlet model', as the Dirichlet multinomial distribution, together with the negative binomial distribution, build up the model.     

NON‐LINEAR DSGE MODELS AND THE CENTRAL DIFFERENCE KALMAN FILTER

This paper introduces a quasi maximum likelihood approach based on the central difference Kalman filter to estimate non‐linear dynamic stochastic general equilibrium (DSGE) models with potentially non‐Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models solved up to third order. These properties are verified in a Monte Carlo study for a DSGE model solved to second and third order with structural shocks that are Gaussian, Laplace distributed, or display stochastic volatility. Copyright © 2012 John Wiley & Sons, Ltd.     

NON‐LINEAR DYNAMICS,COMPLEXITY AND RANDOMNESS: ALGORITHMIC FOUNDATIONS

Abstract In this paper I make an attempt to describe, discuss and extend a few aspects of the rich mathematical tapestry that can be woven with rigorous notions of non‐linear dynamics, complexity and randomness, in terms of algorithmic mathematics. It is a tapestry that I try to weave with economic analysis, economic theory and economic modelling in mind. All three notions – that is, non‐linear dynamics, complexity and randomness – have a rich conceptual, modelling or analytic tradition in core areas of economic theory, both at the micro and macro levels. It is the algorithmic foundation I try to provide for them that could be considered the novel contribution in this paper. Once the algorithmic foundations are in place, it is, for example, almost natural to consider the famed difficulties of obtaining closed form solutions for non‐linear, complex or random dynamic models in economics almost a trivial vestige of a pre‐simulation era in mathematical modelling.     

POSTERIOR‐PREDICTIVE EVIDENCE ON US INFLATION USING EXTENDED NEW KEYNESIAN PHILLIPS CURVE MODELS WITH NON‐FILTERED DATA

Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended New Keynesian Phillips curve (NKPC) models. It is shown that mechanical removal or modeling of simple low‐frequency movements in the data may yield poor predictive results which depend on the model specification used. Basic NKPC models are extended to include structural time series models that describe typical time‐varying patterns in levels and volatilities. Forward‐ and backward‐looking expectation components for inflation are incorporated and their relative importance is evaluated. Survey data on expected inflation are introduced to strengthen the information in the likelihood. Use is made of simulation‐based Bayesian techniques for the empirical analysis. No credible evidence is found on endogeneity and long‐run stability between inflation and marginal costs. Backward‐looking inflation appears stronger than forward‐looking inflation. Levels and volatilities of inflation are estimated more precisely using rich NKPC models. The extended NKPC structures compare favorably with existing basic Bayesian vector autoregressive and stochastic volatility models in terms of fit and prediction. Tails of the complete predictive distributions indicate an increase in the probability of deflation in recent years. Copyright © 2014 John Wiley & Sons, Ltd.     

REAL‐TIME DATA AND FISCAL POLICY ANALYSIS: A SURVEY OF THE LITERATURE

This paper surveys the empirical research on fiscal policy analysis based on real‐time data. This literature can be broadly divided into four groups that focus on: (1) the statistical properties of revisions in fiscal data; (2) the political and institutional determinants of projection errors by governments; (3) the reaction of fiscal policies to the business cycle and (4) the use of real‐time fiscal data in structural vector autoregression (VAR) models. It emerges that, first, fiscal revisions are large and initial releases are biased estimates of final values. Secondly, strong fiscal rules and institutions lead to more accurate releases of fiscal data and smaller deviations of fiscal outcomes from government plans. Thirdly, the cyclical stance of fiscal policies is estimated to be more ‘counter‐cyclical’ when real‐time data are used instead of ex post data. Fourthly, real‐time data can be useful for the identification of fiscal shocks. Finally, it is shown that existing real‐time fiscal data sets cover only a limited number of countries and variables. For example, real‐time data for developing countries are generally unavailable. In addition, real‐time data on European countries are often missing, especially with respect to government revenues and expenditures. Therefore, more work is needed in this field.     

DATA GAPS,DATA INCOMPARABILITY,AND DATA IMPUTATION: A REVIEW OF POVERTY MEASUREMENT METHODS FOR DATA‐SCARCE ENVIRONMENTS

Questions that often come up in contexts where household consumption data are unavailable or missing include: what are the best existing methods to obtain poverty estimates at a single snapshot in time? and over time? and what are the best available methods to study poverty dynamics? A variety of different techniques have been developed to tackle these questions, but unfortunately, they are presented in different forms and lack unified terminology. We offer a review of poverty imputation methods that address contexts ranging from completely missing and partially missing consumption data in cross‐sectional household surveys, to missing panel household data. We present the various existing methods under a common framework, with pedagogical discussion on their intuition. Empirical illustrations are provided using several rounds of household survey data from Vietnam. Furthermore, we also offer a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques.     

SHIFTING SANDS: NON‐LINEARITY,COMPLEXITY AND RANDOMNESS IN ECONOMICS

Abstract The great crash of 2008 and the associated banking crisis have exposed the increasing irrelevance of much mainstream economics and provoked some economists to re‐examine their discipline. Linear or linearized models with well‐behaved additive stochastic disturbances, based on ‘microeconomic foundations’ are no longer anywhere near adequate. Non‐linearity, complexity and randomness cannot be avoided, and the ideas of the British Emergentists have recently been given a new lease of life. Basing economics on algorithmic foundations provides a means of restoring genuine rigour to economics and, it is hoped, allowing the discipline to respond in a rational and humane way the next time a major crisis looms.     

FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH: A META‐ANALYSIS

We analyze 1334 estimates from 67 studies that examine the effect of financial development on economic growth. Taken together, the studies imply a positive and statistically significant effect, but the individual estimates vary widely. We find that both research design and heterogeneity in the underlying effect play a role in explaining the differences in results. Studies that do not address endogeneity tend to overstate the effect of finance on growth. While the effect seems to be weaker in less developed countries, the effect decreases worldwide after the 1980s. Our results also suggest that stock markets support faster economic growth than other financial intermediaries.     

INFLATION AND CENTRAL BANK INDEPENDENCE: A META‐REGRESSION ANALYSIS

Abstract Using 59 studies, we perform a meta‐regression analysis of studies examining the relationship between inflation and central bank independence (CBI). The studies considered are very different with respect to the CBI indicator used, the sample of countries and time periods covered, model specification, estimators used and publication outlet. We conclude that there is a significant publication bias. However, we also find a significant genuine effect of CBI on inflation. Differences between studies are not caused by differences in CBI indicators used.     

GLOBALIZATION AND PRODUCTIVITY: A SURVEY OF FIRM‐LEVEL ANALYSIS

Abstract Recent empirical studies which utilize plant‐ or establishment‐level data to examine globalization's impact on productivity have discovered many causal mechanisms involved in globalization's impact on firms’ productivity. Because these pathways have been broad, there have been few attempts to summarize the several and detailed mechanisms of self‐selection and learning at the same time. This paper examines seven pathways so that the clear‐cut consequences of the broad picture of globalization become visible. This strategy is useful for detecting missing links within and across the existing studies as well as for finding possible synergy effects among different mechanisms. Insightful policy implications may be derived from the comprehensive comparisons between the seven different pathways of globalization.     

THE FINANCIAL DEVELOPMENT AND GROWTH NEXUS: A META‐ANALYSIS

We conduct a meta‐analysis of the literature of financial development and economic growth. We cover a large number of empirical studies and estimations that have been published in journal articles. We measure the degree of heterogeneity and identify the causes of the observed differentiation. Among the most significant factors behind this heterogeneity is the choice of financial‐variable proxies, the kind of data used as well as whether a study takes into account the issue of endogeneity. Our results suggest that the empirical literature on the finance–growth nexus is not free from publication bias. Also, a genuine positive effect exists between financial development and economic growth.     

CHILD CARE PRICES AND MATERNAL EMPLOYMENT: A META‐ANALYSIS

The literature estimates for labor force participation elasticity with regard to child care prices are extensive and varying. While some estimates imply substantial gains from child care subsidies, others find insignificant effects. To determine the causes of the variance, this paper reviews and analyzes the elasticity sizes using estimates from 36 peer‐reviewed articles and working papers in the literature. We start by reviewing the theoretical and empirical aspects related to participation elasticity with regard to child care costs, paying special attention to sample characteristics, methodological aspects, and macro level factors. We conclude by providing a meta‐regression using control variables based on our review of the literature to explain some of the differences between the estimates. As research builds on and improves the methods and assumptions in prior works, elasticity estimates have become smaller over time. This decline might also be partially explained by changes in labor market characteristics. In countries with high rates of part‐time work and very high or very low rates of female labor force participation, we find elasticity rates to be smaller.     

MULTIPLE TESTING AND HETEROGENEOUS TREATMENT EFFECTS: RE‐EVALUATING THE EFFECT OF PROGRESA ON SCHOOL ENROLLMENT

The effect of a program or treatment may vary according to observed characteristics. In such a setting, it may not only be of interest to determine whether the program or treatment has an effect on some sub‐population defined by these observed characteristics, but also to determine for which sub‐populations, if any, there is an effect. This paper treats this problem as a multiple testing problem in which each null hypothesis in the family of null hypotheses specifies whether the program has an effect on the outcome of interest for a particular sub‐population. We develop our methodology in the context of PROGRESA, a large‐scale poverty‐reduction program in Mexico. In our application, the outcome of interest is the school enrollment rate and the sub‐populations are defined by gender and highest grade completed. Under weak assumptions, the testing procedure we construct controls the familywise error rate—the probability of even one false rejection—in finite samples. Similar to earlier studies, we find that the program has a significant effect on the school enrollment rate, but only for a much smaller number of sub‐populations when compared to results that do not adjust for multiple testing. Copyright © 2013 John Wiley & Sons, Ltd.     

THE CONTINUOUS WAVELET TRANSFORM: MOVING BEYOND UNI‐ AND BIVARIATE ANALYSIS

A body of work using the continuous wavelet transform has been growing. We provide a self‐contained summary on its most relevant theoretical results, describe how such transforms can be implemented in practice, and generalize the concept of simple coherency to partial wavelet coherency and multiple wavelet coherency, moving beyond bivariate analysis. We also describe a family of wavelets, which emerges as an alternative to the popular Morlet wavelet, the generalized Morse wavelets. A user‐friendly toolbox, with examples, is attached to this paper.     

MULTI‐CRITERIA OPTIMIZATION OF REGIONAL EMPLOYMENT POLICY: A SIMULATION ANALYSIS FOR GERMANY

The distribution of European and national aid among 271 German labor market regions is considered as an optimization problem with three targets: (i) interregional equalization of unemployment rates; (ii) minimization of total (national) unemployment; and (iii) maximization of GDP, subject to budget constraints and some administrative restrictions. The analysis of the German program in 2000–2002 shows that the results actually obtained for 6 billion euro required only 241 million euro under optimal planning (4% of the actual budget). Such an inappropriate implementation of active labor market policies can be the cause of low efficiency, often misinterpreted as uselessness. This paper suggests a decision aid for optimal planning and shows that tax returns from the additional GDP due to jobs subsidized can transform regional policy into a winning governmental strategy.