Impact evaluation of multiple overlapping programs under a conditional independence assumption

Under the assumption on conditional independence between potential outcomes and program assignment, program impacts measured by the Average Treatment Effect (ATE) and the Average Treatment Effect on Treated (ATT) can be identified and estimated using cross-section regression or propensity score matching (PSM). Traditional impact literature often deals with the impact evaluation of a single program. In reality, one can participate in several programs simultaneously and the programs may be correlated. This paper discusses cross-section regression and PSM methods in this general context. It is shown that under the PSM method, impact of a program of interest can be measured as a weighted average of program impacts on groups with different program statuses. Estimation of impacts of multiple overlapping programs is illustrated using Monte Carlo simulation and an empirical example of impact measurement of international and internal remittances in Vietnam.     

Persistence and economic effects of technological innovations: a dynamic and sequential analysis of Uruguayan manufacturing firms

This paper analyzes the long-term relationship between research and development (R&D), innovations and productivity in 400 Uruguayan manufacturing firms during the period 2001–2009 based on a modified version of the structural model of Crepon, Duguet and Mairesse. The paper also analyzes thoroughly the decision of these firms to engage in R&D activities by using a novel categorical dependent variable, which takes three values: non-performance R&D activities, occasional performance or continuous performance over the period. Furthermore, the study investigates whether these manufacturing ?rms innovate persistently or discontinuously over the period. The results suggest a positive link between the intensity of R&D activities and the generation of product and process innovations. They also indicate that innovation probability is temporally persistent at the ?rm-level only for product innovations. Finally, the empirical findings reveal that these technological innovations have a positive effect on firm’s productivity.     

The effects of IMF conditional programs on the unemployment rate

The fundamental mission of the International Monetary Fund (IMF) is to ensure global financial stability and to assist countries in economic turmoil. Although there is a consensus that IMF-supported programs can have a direct effect on the labor market of recipient countries, it remains unclear how IMF participation decision and conditionalities attached to IMF loans can affect the unemployment rate of borrowing countries. Using a world sample of countries from 1980 to 2014, we investigate how lending conditional programs of the IMF affect the unemployment rate. Our analyses account for the selection bias related to, first, the IMF participation decision and, second, the conditions included within the program. We show that IMF program participation significantly increases the unemployment rate of recipient countries. Once we control for the number of conditions, however, we find that only IMF conditions have a detrimental and highly significant effect on the unemployment rate. There is evidence that the adverse short-run effect of IMF conditions holds robust in the long-run. Disaggregating IMF conditionality by issue area, we find adverse effects on the unemployment rate for four policy areas: labor market deregulation, reforms requiring privatization of state-owned enterprises, external sector reforms stipulating trade and capital account liberalization, and fiscal policy reforms that restrain government expenditure. Our initial results are found to be robust across alternative empirical specifications.     

Analysis of contagion from the dynamic conditional correlation model with Markov Regime switching

Over the last decades, the transmissions of international financial events have been the subject of many academic studies focused on multivariate volatility models. This study evaluates the financial contagion between stock market returns. The econometric model employed, regime switching dynamic correlation (RSDC). A modification was made in the original RSDC model, the introduction of the GJR-GARCH-N and also GJR-GARCH-t models, on the equation of conditional univariate variances, thus allowing us to capture the asymmetric effects in volatility and also heavy tails. A database was built using series of indices in the United States (S&P500), the United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) from 1 February 2003 to 20 September 2012. Throughout this study the methodology is compared with those frequently found in literature, and the model RSDC with two regimes was defined as the most appropriate for the selected sample with t-Student distribution in the disturbances. The adapted RSDC model used in this article can be used to detect contagion – considering the definition of financial contagion from the World Bank called very restrictive – with the help of the empirical exercise.     

Volatility and dynamic conditional correlations of worldwide emerging and frontier markets

This study examines the relationship between time-varying correlations and conditional volatility among 32 worldwide emerging and frontier stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging and frontier markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in most countries. Thus, diversification benefits decrease during periods of higher volatility.     

Deriving conditional and unconditional marginal effects in log earnings equations estimated by Heckman's procedure

Although the Heckman approach has often been used in empirical analysis, the marginal effects, necessary to interpret the effect of the regressors on the dependent variable, appeared to be overlooked. Using the Heckman approach, general expressions are derived for calculating the conditional and unconditional marginal effects. Based on a sample of Brazilian women, the conditional and unconditional return to education are calculated for the logarithm of earnings equation estimated by Heckman's procedure, comparing them to the marginal effect of education obtained without correcting for selectivity bias. The same analysis is carried out for a discrete variable ‘black’.     

Analysis of electricity prices for Central American countries using dynamic conditional score models

In this paper, we compare the performance of dynamic conditional score (DCS) and standard financial time-series models for Central American energy prices. We extend the Student’s t and the exponential generalised beta distribution of the second kind stochastic location and stochastic seasonal DCS models. We consider the generalised t distribution as an alternative for the error term and also consider dynamic specifications of volatility. We use a unique dataset of spot electricity prices for El Salvador, Guatemala and Panama. We consider two data windows for each country, which are defined with respect to the liberalisation and development process of the energy market in Central America. We study the identification of a wide range of DCS specifications, likelihood-based model performance, time-series components of energy prices, maximum likelihood parameter estimates, the discounting property of conditional score, and out-of-sample forecast performance. Our main results are the following. (i) We determine the most robust models of energy prices, with respect to parameter identification, from a wide range of DCS specifications. (ii) For most of the cases, the in-sample statistical performance of DCS is superior to that of the standard model. (iii) For El Salvador and Panama, the standard model provides better point forecasts than DCS, and for Guatemala the point forecast precision of standard and DCS models does not differ significantly. (iv) For El Salvador, the standard model provides better density forecasts than DCS, and for Guatemala and Panama, the density forecast precision of standard and DCS models does not differ significantly.     

Extrapolation of causal effects – hopes,assumptions, and the extrapolator’s circle

ABSTRACT

I consider recent strategies proposed by econometricians for extrapolating causal effects from experimental to target populations. I argue that these strategies fall prey to the extrapolator’s circle: they require so much knowledge about the target population that the causal effects to be extrapolated can be identified from information about the target alone. I then consider comparative process tracing (CPT) as a potential remedy. Although specifically designed to evade the extrapolator’s circle, I argue that CPT is unlikely to facilitate extrapolation in typical econometrics and evidence-based policy applications. To argue this, I offer a distinction between two kinds of extrapolation, attributive and predictive, the latter being prevalent in econometrics and evidence-based policy. I argue that CPT is not helpful for predictive extrapolation when using the kinds of evidence that econometricians and evidence-based policy researchers prefer. I suggest that econometricians may need to consider qualitative evidence to overcome this problem.     

On the measurement of dynamic effects of integration

By allowing a freer interplay of market forces, the market liberalization involved in closer economic integration can improve the efficiency of productive factors. This permits greater output from the same inputs. A side effect of this improved efficiency is an improved investment climate in the integrating region. This in turn will result in a higher investment rate, thereby augmenting the initial output gains by providing the economy with more resources. The same sort of induced capital formation can also boost investment in human capital and knowledge capital. Primitive calculations of the size and timing of these induced capital formation can be made using an aggregate GDP function. A rough approximation of the adjustment path shows that the extra investment will stimulate growth for decades, although half of the total effect will occur in the first 10 to 50 years.     

Heterogeneity in the dynamic effects of uncertainty on investment

We examine how aggregate profit uncertainty influences capital investment activities, focusing on heterogeneous responses of firms. We model aggregate profit uncertainty as the conditional standard deviation of a common factor across unforecasted fluctuations in the sales growth of different industries and exploit cross‐sectional variations for its estimation. From an investment forecasting model that coherently analyzes firm‐ or group‐specific effects of uncertainty, we find that the direction and the size of investment adjustment vary considerably across firms, with a significant but small negative average impact. Our results highlight the importance of accounting for heterogeneity in the transmission of uncertainty, allowing us to reconcile different views on the effect of uncertainty in the existing literature.     

Modelling the effects of protection in a dynamic framework

The effects of alternative trade strategies on development performance are analyzed using a small, dynamic, computable general equilibrium model. The static allocation costs of protection are quantitatively weighed against the dynamic benefits resulting from heterogenous capital goods and imperfect foresight. An attempt at quantifying the effects of protection on employment and savings behavior is made by using submodels specifying distortions in labor-markets and alternative savings functions.     

Differentiability of the value function without interiority assumptions

This paper studies first-order differentiability properties of the value function in concave dynamic programs. Motivated by economic considerations, we dispense with commonly imposed interiority assumptions. We suppose that the correspondence of feasible choices varies with the vector of state variables, and we allow the optimal solution to belong to the boundary of this correspondence. Under minimal assumptions we prove that the value function is continuously differentiable. We then discuss this result in the context of some economic models, and focus on some examples in which our assumptions are not met and the value function is not differentiable.     

On the evolution of conditional cooperation

A long series of laboratory and field experiments, as well as conventional empirical studies, has established that (1) individuals voluntarily provide themselves with public goods at levels exceeding those predicted by the Nash voluntary contributions mechanism, and (2) agents reciprocate increases in the contributions of their counterparts in such settings (conditional cooperation). This paper presents a simple model of the evolution of preferences for conditional cooperation in the presence of a public good, which explains these two empirical findings without employing reputational or group selection arguments. In this model, individuals inherit preferences to match other agents' contributions to the provision of a public good, at some specified “matching rate.” Agents whose preferences induce them to be relatively successful – in material terms – increase in number, from one generation to the next. Under complete information and with randomly matched groups of N agents who have quasilinear preferences over the public good and a private good, the unique evolutionarily stable matching rate is 1, leading to Pareto optimal voluntary provision of the public good, regardless of group size N. The evolutionarily stable matching rate can be viewed as an endogenous social norm.     

An assessment of the dynamic effects of monetary policy in Macedonia

Macedonia, as a small emerging economy, is exposed to foreign risks such as: exchange rate volatility, trade distortions, and highly volatile capital flows. To ‘protect’ its economy, since 1995, the Macedonian Central Bank has applied the monetary strategy of exchange rate targeting, where the interest rate on Central Bank bills auctions is a basic monetary-policy instrument. This paper re-examined the effectiveness of the current monetary policy in Macedonia using the policy-oriented vector error correction model (VECM). We found that the Macedonian Central Bank demonstrates a low level of monetary-policy effectiveness and the existing monetary-policy strategy does not necessarily promote its ability to react countercyclically.     

我国农产品实施绿色营销的思路

本文提出我国农产品实施绿色营销是重要的战略选择，分析了实施农产品绿色营销的体系，并提出实施绿色营销战略的基本思路。     

Equilibria in a dynamic global game: the role of cohort effects

Summary. We introduce strategic waiting in a global game setting with irreversible investment. Players can wait in order to make a better informed decision. We allow for cohort effects, which arise endogenously in technology adoption problems with positive contemporaneous network effects. Formally, cohort effects lead to intra-period network effects being greater than inter-period network effects. Depending on the nature of the cohort effects, our game may or may not satisfy dynamic increasing differences. If it does, our model has a unique rationalizable outcome. Otherwise, multiple equilibria may exist as players want to invest at the same point in time others do.Received: 13 July 2004, Revised: 20 May 2005, JEL Classification Numbers: C72, C73, D82, D83.We thank George-Marios Angeletos, Helmut Bester, Andreas Blume, Estelle Cantillon, Frank Heinemann, Christian Hellwig, Larry Karp, Tobias Kretschmer, In Ho Lee, Robin Mason and an anonymous referee for helpful comments. We also thank seminar participants at the EEA-meeting in Stockholm 2003, ESRC Workshop in Warwick 2004, Free University Berlin, IAE (Barcelona), Keele, MIT, Southampton, University of Pittsburgh, and at a CEPR-conference in Brussels 2002 for comments, and the European Union for providing financial support through the TMR network on network industries (Contract number FMRX-CT98-0203). This paper was completed while the first author visited the Department of Economics at MIT, whose hospitality he gratefully acknowledges.     

On the role of the production and consumption assumptions for optimum taxation

The sensitivity of optimum tax rates to a variety of factors has sustained many different lines of enquiry. This paper attempts to demonstrate by computational procedures the role of the production and consumption–leisure assumptions in the light of recent research. In particular the work of Stern will be extended to provide an assessment of the Allen analysis. It will be shown that optimum negative marginal tax rates are no longer a curiousity and that our production and consumption–leisure assumptions are of considerable importance for variable wage tax models.     

Development of the extended linear expenditure system from simple saving assumptions

The extended linear expenditure system (ELES) can be developed as an atemporal maximization of a Stone-Geary utility function wherein saving is treated as a good in itself. The key to this development is the a priori specification of the ‘subsistence quantity’ of saving, γ_{n + 1}, to be zero. Thus, the intertemporal maximization approach to the ELES is equivalent to specifying a Klein-Rubin saving function with γ_{n + 1} = 0 for a linear expenditure system (LES) based on permanent income rather than total expenditure. Any income concept - current, normal, or permanent, for example - is acceptable for the ELES developed from the atemporal maximization.