Investment-specific shocks and real business cycles in emerging economies: Evidence from Brazil

This paper investigates the role of the RBC (Real Business Cycle) model with investment-specific technology shocks in explaining business cycle fluctuations in Brazil. I consider the role of transitory and permanent components of neutral and investment-specific technology shocks. I fit the model to the data using Bayesian techniques to show that the investment-specific shocks are important sources of fluctuations in the estimated model. In fact, in the context of the model, investment-specific shocks can account for remarkable percentages of fluctuations in consumption growth, GDP growth, investment growth and trade balance to GDP ratio. Furthermore, I present simulation evidence showing that the RBC model cannot account for some important features of the data.     

Cyclical wage movements in emerging markets compared to developed economies: The role of interest rates

This paper documents that, at the aggregate level, (i) real wages are positively correlated with output and, on average, lag output by about one quarter in emerging markets, while there are no systematic patterns in developed economies, and (ii) real wage volatility (relative to output volatility) is about twice as high in emerging markets compared with developed economies. We then present a small open economy model with productivity shocks and countercyclical interest rates. The model incorporates a working capital requirement and the Jaimovich and Rebelo (2009) preference that allows for flexible parameterization of the strength of income effects on labor supply. The model can account for the high volatility of wage and consumption relative to output and countercyclical trade balances that characterize emerging-market economies. During economic downturns, rising interest rates in emerging markets induce relatively large income effects on labor supply, so households would not reduce their labor input as much even though wages drop significantly.     

Cost-based Phillips Curve forecasts of inflation

It is a well-established idea that prices are a function of marginal cost, yet estimating a reliable measure of marginal cost is difficult to do. Stock and Watson (1999) use the Phillips Curve to forecast inflation for a variety of existing activity variables that researchers commonly use to proxy for marginal cost. This paper uses a similar type of approach to examine the performance of a new candidate for the activity variable, which is marginal cost measured following the theoretical methodology of Bils (1987), which we find to be simple yet powerful when implemented empirically. We then use the Phillips Curve to conduct pseudo out-of-sample inflation forecasts for the US using: output, unemployment, hours, the labor share, the capacity utilization rate, and the new measure of marginal cost. For almost all cases, forecast errors are lowest in the regressions with the new marginal cost variable, indicating that this new measure is an improvement over previous attempts to proxy for marginal cost.     

Did monetary or technology shocks move euro area stock prices?

Using a Bayesian vector autoregressive (VAR) model, I investigate the impact of monetary and technology shocks on the euro area stock market. I find an important role for technology surprise shocks, but not monetary shocks, in explaining variations in real stock prices. Specifically, the pronounced boom?Cbust cycle of 1995?C2003 is largely due to technology surprise shocks. The identification method allows me to study the effects of technology news shocks. The responses are consistent with the idea that news on technology improvements has an immediate impact on stock prices. These findings are robust to several modelling choices, including the productivity measure, the specification of the VAR model, and the identifying restrictions.     

Large deviations and multinomial probit choice

We consider a discrete choice model in which the payoffs to each of an agent?s n actions are subjected to the average of m i.i.d. shocks, and use tools from large deviations theory to characterize the rate of decay of the probability of choosing a given suboptimal action as m approaches infinity. Our model includes the multinomial probit model of Myatt and Wallace (2003) [5] as a special case. We show that their formula describing the rates of decay of choice probabilities is incorrect, provide the correct formula, and use our large deviations analysis to provide intuition for the difference between the two.     

Macroeconomics,finance, commodities: Interactions with carbon markets in a data-rich model

This article assesses the transmission of international shocks to EUA spot, EUA futures, and CER futures carbon prices using a broad dataset that includes 115 macroeconomic, financial and commodities indicators with daily frequency from April 4, 2008 to January 25, 2010 totalling 463 observations. The framework adopted is a Factor-Augmented Vector Autoregression model with latent factors extracted from the dataset, as proposed by Bernanke et al. (2005). The main results can be summarized as follows. First, based on impulse responses, we show that carbon prices tend to respond negatively (between ? 0.2 and ? 1.2 standard deviation) to an exogenous shock that reduces global economic indicators by one standard deviation. Second, we find evidence that the responses are heterogeneous among the different kinds of carbon prices: CER futures prices tend to react much more significantly than EUA spot and futures prices. Third, the factors explain about 50% of the total variance of all variables in the dataset. The largest contribution is accounted for by the factor correlated with commodities markets, which explains about 28% of the total variability.     

Relationship between management ownership and firm value among the business group affiliated firms in Korea

In this paper, we revisit an old issue on the relation between management ownership and firm’s value. The Korean panel data on the business group firms, allows us to compute ownership right and control right separately for each business group affiliated firm. Our measures are different from the similar measures on the Korean firms as in Baek et al. (2004) or Joh (2003). Rather than confounding the two offsetting effects, this paper tests convergence of interest hypothesis and entrenchment hypothesis separately. Empirical findings show that, given control right, there is no clear-cut relation between firm value and the inside management ownership for most firms with the inside management ownership less than 42%, that there is a positive relation between firm value and the inside management ownership for those firms with the inside management ownership higher than 42%, and that, given ownership right, profitability decreases as control right increases.     

Modeling unemployment as an inventory: A multicointegration approach

We examine the dynamic phenomenon of unemployment as a constantly changing inventory of unemployed individuals. We focus on the possibility raised by Elsby et al. (2009) of an innate “inseparability” between the flows into and out of unemployment. Multicointegration, introduced by Granger and Lee (1989), offers a natural way to model the level of unemployment as an inventory. We find that there is multicointegration between inflows into and outflows from unemployment and the level of unemployment itself. By identifying this multicointegrating relationship, we are able to specify an error correction model for unemployment, improving forecasting ability.     

Sector-specific productivity shocks in a matching model

Endogenous separation matching models have the shortcoming that they are barely able to replicate the Beveridge curve (i.e. the negative correlation between unemployment and vacancies) and business cycle statistics jointly. This paper builds upon the sectoral shock literature and combines its insights with the standard endogenous separation matching approach. We show that the endogenous matching model with sectoral shocks can generate an aggregate Beveridge curve and performs reasonably well in explaining business cycle facts, especially compared to the one-sector baseline model.     

Biogeographical conditions, the transition to agriculture and long-run growth

We use new data on the timing of the transition to agriculture, developed by Putterman and Trainor (2006), to test the theory of Diamond (1997) and Olsson and Hibbs (2005) that an earlier transition is reflected in higher incomes today. Our results confirm the theory, even after controlling for institutional quality and other geographical factors. The date of transition is correlated with prehistoric biogeography (the availability of wild grasses and large domesticable animal species). The factors conducive to high per capita incomes today are good institutions, an early transition to agriculture, access to the sea and a low incidence of fatal malaria. Geographical influences have been at work in all of these proximate determinants of per capita income.     

Technology shocks, structural breaks and the effects on the business cycle

It is shown that time-series of US productivity and hours are apparently affected by a structural break in the late 60s. Moreover, the importance of technology shocks over the business cycle has sharply decreased after the break.     

Monetary business cycle accounting

This paper investigates the quantitative importance of various types of distortions for inflation and nominal interest rate dynamics by extending business cycle accounting to monetary models. Representing various classes of real and nominal distortions as ‘wedges’ in standard equilibrium conditions allows a quantitative assessment of those distortions. Decomposing the data into movements due to these wedges shows that distortions generating movements in TFP and wedges in equilibrium conditions for asset markets are essential. In contrast, wedges capturing the effects of sticky prices play less important role. These results are robust to alternative implementations of the accounting method.     

Optimal stopping with dynamic variational preferences

We solve optimal stopping problems in uncertain environments for agents assessing utility by virtue of dynamic variational preferences as in Maccheroni, Marinacci and Rustichini (2006) [16] or, equivalently, assessing risk in terms of dynamic convex risk measures as in Cheridito, Delbaen and Kupper (2006) [4]. The solution is achieved by generalizing the approach in Riedel (2009) [21] introducing the concept of variational supermartingales and variational Snell envelopes with an accompanying theory. To illustrate results, we consider prominent examples: dynamic multiplier preferences and a dynamic version of generalized average value at risk introduced in Cheridito and Tianhui (2009) [5].     

Labor Market Dynamics and the Business Cycle: Structural Evidence for the United States*

We use a 12‐dimensional VAR to examine the aggregate effects of two structural technology shocks and two policy shocks. For each shock, we examine the dynamic effects on the labor market, the importance of the shock for labor market volatility, and the comovement between labor market variables and other key aggregate variables in response to the shock. We document that labor market indicators display “hump‐shaped” responses to the identified shocks. Technology shocks and monetary policy shocks are important for labor market volatility but the ranking of their importance is sensitive to the VAR specification. The conditional correlations at business cycle frequencies are similar in response to the four shocks, apart from the correlations between hours worked, labor productivity and real wages. To account for the unconditional correlations between these variables, a mixture of shocks is required.     

A new test for linear inequality constraints when the variance–covariance matrix depends on the unknown parameters

We extend Hansen’s (2005) test to testing hypotheses involving general inequality constraints where the variance–covariance matrix of the functions in the constraints depends on the unknown parameters. The test can be applied to a wider class of problems than Wolak’s (1991).     

Nominal inertia and shock persistence in UK business cycles

A structural VAR methodology is used for UK data to identify and map out the effects of innovations in the money supply, employment, output, wages and prices. Moreover, bands of two standard errors are computed for the impulse response functions so that comment may be made on the significance of the dynamic responses of the variables to the simulated shocks. This allows conclusions to be drawn on the persistence of shocks. Results suggest that output variation is largely determined by aggregate demand shocks over the business cycle frequency. Importantly, evidence is also found of rigidities in the form of price inertia and nominal wage stickiness.     

Avoiding pitfalls in using structural VARs to estimate economic models

Structural Vector Autoregressions with a differenced specification of hours (DSVAR) suggest that productivity shocks identified using long-run restrictions lead to a persistent and significant decline in hours worked. Economists have interpreted this evidence as showing that standard business cycle models in which a positive technology shock leads to a rise in hours are inconsistent with the data. In this paper we argue that such a conclusion is unwarranted because model's data and actual data are not treated symmetrically. To illustrate this problem, we estimate and test a flexible-price DSGE model with non-stationary hours using Indirect Inference on impulse responses of hours and output after technology and non-technology shocks. We find that, once augmented with a moderate amount of real frictions, the model can mimic well impulse responses obtained from a DSVAR on actual data. Using this model as a data generating process, we show that our estimation method is less subject to bias than a method that would directly compare theoretical responses with responses from the DSVAR.     

Real business cycles, sticky wages or sticky prices? The impact of technology shocks on US manufacturing

In this paper, we examine empirically the predictions of a range of theoretical models which give a prominent role to technology shocks in explaining business cycles. To this end, we estimate (4-digit SIC) industry-level VAR models for US manufacturing using real output, the real wage and utilization corrected measures of technology and labor input. Our results support both sticky-wage DGE and RBC models over sticky-price DGE models. Moreover, they cast some doubt on the importance of technology shocks as propulsive mechanism for business cycles at the industry level.     

Cross-country causes and consequences of the crisis: An update

We update [13] and [Rose and Spiegel, 2010] and search for simple quantitative models of macroeconomic and financial indicators of the “Great Recession” of 2008–09. We use a cross-country approach and examine a number of potential causes that have been found to be successful indicators of crisis intensity by other scholars. We check a number of different indicators of crisis intensity, and a variety of different country samples. While countries with higher income and looser credit market regulation seemed to suffer worse crises, we find few clear reliable indicators in the pre-crisis data of the incidence of the Great Recession. Countries with current account surpluses seemed better insulated from slowdowns.     

The recent boom–bust cycle: The relative contribution of capital flows, credit supply and asset bubbles

We use an estimated open economy DSGE model with financial frictions for the US and the rest of the world to evaluate various competing explanations about the recent boom–bust cycle. We find that the savings glut hypothesis is insufficient for explaining all aspects of the boom in the US. Relatively strong TFP growth and expansionary monetary policy are also not able to explain fully the volatility of corporate and in particular residential investment. We identify bubbles in the stock and housing market as crucial. Concerning the downturn in 2008/2009, the fall in house prices and residential investment only plays a minor role. Mortgage defaults have more explanatory power, especially in a specification of the model with a segregated equity market. Finally, the bursting of the stock market bubble was at least as important in this recession as in 2001. Because of various negative shocks hitting the economy at the same time in 2008/2009 and continued positive technology growth, not only the real interest rate declined but inflation fell rapidly and left insufficient room for monetary policy to play a similar stabilising role as in previous recessions.