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This paper analyzes labor market responses to productivity shocks when firms set employment criteria on the basis of the likelihood of hiring high or low productivity workers. In response to a positive productivity shock, firms do not raise the criterion as much as the shock, increasing the proportion of low productivity workers among the employed. The observed average productivity may respond negligibly even if employment changes substantially. Interest rate fluctuations can yield an opposite relation between productivity and employment, explaining the weak empirical relationship.

In this chapter, using a combination of long-run and sign restrictions to identify aggregate monetary and productivity factors, I find that the monetary factor is responsible for long swings in nominal variables but has little effect on fluctuations in output, real wage, or labor input growth. The productivity factor in addition to increasing output growth and real wage growth in the short and long run, also results in increases in labor input and decreases in prices, but the quantitative effect of the productivity factor on labor input is relatively small. These results are robust to the number of factors included in the model and to alternative priors about the short-run effects of the monetary factor, and to the inclusion of oil prices. Oil prices, in fact, appear to be largely driven by the other aggregate factors.

The global slack hypothesis is central to the discussion of the trade-offs that monetary policy faces in an increasingly more integrated world. The workhorse New Open Economy Macro (NOEM) model of Martínez-García and Wynne (2010), which fleshes out this hypothesis, shows how expected future local inflation and global slack affect current local inflation. In this chapter, I propose the use of the orthogonalization method of Aoki (1981) and Fukuda (1993) on the workhorse NOEM model to further decompose local inflation into a global component and an inflation differential component. I find that the log-linearized rational expectations model of Martínez-García and Wynne (2010) can be solved with two separate subsystems to describe each of these two components of inflation.

I estimate the full NOEM model with Bayesian techniques using data for the United States and an aggregate of its 38 largest trading partners from 1980Q1 until 2011Q4. The Bayesian estimation recognizes the parameter uncertainty surrounding the model and calls on the data (inflation and output) to discipline the parameterization. My findings show that the strength of the international spillovers through trade – even in the absence of common shocks – is reflected in the response of global inflation and is incorporated into local inflation dynamics. Furthermore, I find that key features of the economy can have different impacts on global and local inflation – in particular, I show that the parameters that determine the import share and the price-elasticity of trade matter in explaining the inflation differential component but not the global component of inflation.

A state space representation of a linearized DSGE model implies a VAR in terms of observable variables. The model is said be non-invertible if there exists no linear rotation of the VAR innovations which can recover the economic shocks. Non-invertibility arises when the observed variables fail to perfectly reveal the state variables of the model. The imperfect observation of the state drives a wedge between the VAR innovations and the deep shocks, potentially invalidating conclusions drawn from structural impulse response analysis in the VAR. The principal contribution of this chapter is to show that non-invertibility should not be thought of as an “either/or” proposition – even when a model has a non-invertibility, the wedge between VAR innovations and economic shocks may be small, and structural VARs may nonetheless perform reliably. As an increasingly popular example, so-called “news shocks” generate foresight about changes in future fundamentals – such as productivity, taxes, or government spending – and lead to an unassailable missing state variable problem and hence non-invertible VAR representations. Simulation evidence from a medium scale DSGE model augmented with news shocks about future productivity reveals that structural VAR methods often perform well in practice, in spite of a known non-invertibility. Impulse responses obtained from VARs closely correspond to the theoretical responses from the model, and the estimated VAR responses are successful in discriminating between alternative, nested specifications of the underlying DSGE model. Since the non-invertibility problem is, at its core, one of missing information, conditioning on more information, for example through factor augmented VARs, is shown to either ameliorate or eliminate invertibility problems altogether.

Open-Economy models are central to the discussion of the trade-offs monetary policy faces in an increasingly more globalized world (e.g., Marínez-García & Wynne, 2010), but bringing them to the data is not without its challenges. Controlling for misspecification bias, we trace the problem of uncertainty surrounding structural parameter estimation in the context of a fully specified New Open Economy Macro (NOEM) model partly to sample size. We suggest that standard macroeconomic time series with a coverage of less than forty years may not be informative enough for some parameters of interest to be recovered with precision. We also illustrate how uncertainty also arises from weak structural identification, irrespective of the sample size. This remains a concern for empirical research and we recommend estimation with simulated observations before using actual data as a way of detecting structural parameters that are prone to weak identification. We also recommend careful evaluation and documentation of the implementation strategy (specially in the selection of observables) as it can have significant effects on the strength of identification of key model parameters.

This paper aims to investigate the effects of a multifaceted negative Russian export shock of 2014 on the exports Estonian firms that exported non-embargoed goods to Russia.

The dataset covers all the Estonian exporters that exported non-embargoed goods to Russia in 2013 and the empirical analysis uses a difference-in-difference method in combination with the coarsened exact matching method to account for heterogeneities between the treatment and control groups.

The empirical findings show that wholesalers affected were generally able to show better export performance after the negative shock than direct exporters were. The trade performance after the shock was lower for both wholesalers and direct exporters that had lower initial productivity levels.

As a novelty, this study simultaneously addresses several firm heterogeneities to illustrate how the trade effects of a negative export shock differ between firms with different key characteristics, including between wholesalers and direct exporters.

The aim of the study is to investigate the relative significance of the determinants of disaggregated capital flows (foreign direct investment and portfolio flows) to five developing countries, across different time horizons.

An empirically tractable structural VAR model of the determinants of capital flows is developed, and variance decomposition and impulse response analyses are used to investigate the temporal dynamic effects of shocks to push and pull factors on foreign direct investment and portfolio flows.

Estimation of the model using quarterly data for the period 1976‐2001 provides evidence supporting the hypothesis that shocks to real variables of economic activity such as foreign output and domestic productivity are the most important forces explaining the variations in capital flows to developing countries.

These findings highlight the concomitant need for policy makers in developing countries to design domestic policy that accounts for both external and internal shocks to real variables of economic activity.

Previous empirical studies on the determinants of capital flows to developing countries have mostly examined the capital flow variable in aggregate, and have largely overlooked the possibility that the relative significance of estimated coefficients of such determinants may vary across time horizons.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

The purpose of this paper is to identify factors behind cyclical fluctuations and differences in adjustments to shocks in Greece, Italy, Portugal and Spain (GIPS) and a reference country – Germany. The authors try to answer the question whether the GIPS countries could have fared differently in the Great Recession if they reacted to shocks affecting them like a resilient German economy would have.

The authors use a DSGE model of real open economy with search and matching on the labour market and endogenous job destruction, estimated separately for each country. The authors calculate impulse response functions, historical decompositions and perform counterfactual simulations of the response of the German model to the sequence of shocks identified for each of GIPS.

The authors find that all GIPS countries were more vulnerable to productivity and foreign demand shocks than Germany. They would have experienced lower macroeconomic volatility if they reacted to their shocks like Germany. Employment (unemployment) rates in GIPS would have been less volatile and higher (lower) during the Great Recession, especially in Spain and Greece. Real wage volatility would have been higher, especially in Spain and Portugal.

The trade-off between unemployment and wage adjustments vis-à-vis Germany was the largest in Spain, which also would have experienced lower variability of job separations and hirings. The evolution of the labour market in Greece and Portugal was driven rather by its higher responsiveness to GDP fluctuations than in Germany, whereas Italy emerges as the least responsive labour market within GIPS.