Measuring total productivity change

This paper examines several ways of measuring the aggregate rate of technical change: with the aggregate production function; in a disaggregated framework of the multisector model; and with the net social production possibility frontier or the generalized factor price frontier. Conditions under which all three approaches are mutually compatible are determined.     

Heterogeneous labor and the dynamics of aggregate labor demand: Some estimations using panel data

In this article we pay attention to the conditions that make an aggregate labor demand equation consistent with the underlying model at a more disaggregated level when heterogeneity exists across firms or across workers. It is argued that this consistency rests on the condition that employment evolves in the same direction in all firms and for all skill levels.Moreover, it is shown empirically that even though the above condition is satisfied, satisfactory estimations of an aggregated model can hide misspecification problems that become apparent when one also estimates the underlying disaggregated models.     

Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon

This work aims to compare the forecast efficiency of different types of methodologies applied to Brazilian consumer inflation (Índice de Preços ao Consumidor Amplo; IPCA). We will compare forecasting models using disaggregated and aggregated data from IPCA over 12 months ahead. We used IPCA in a monthly basis, over the period between January 1996 and March 2012. Out-of-sample analysis will be made through the period of January 2008 to March 2012. The disaggregated models were estimated by Seasonal Autoregressive Integrated Moving Average (SARIMA) and will have different levels of disaggregation from IPCA as groups and items, as well as disaggregation with more economic sense used by Brazilian Central Bank as: (1) services, monitored prices, food and industrials and (2) durables, non-durables, semi-durables, services and monitored prices. Aggregated models will be estimated by time series techniques as SARIMA, state-space structural models and Markov-switching. The forecasting accuracy among models will be made by the selection model procedure known as Model Confidence Set developed by Peter Hansen, Asger Lunde and James Nason. We were able to find evidence of forecast accuracy gains in models using more disaggregated rather than aggregate data.     

The ins and outs of unemployment in Canada, 1976–2008

Abstract This paper studies the flows into and out of unemployment in Canada at an aggregate and a number of disaggregated levels. I find that inflows into unemployment are countercyclical and outflows are procyclical. At an aggregate level, changes in the rate at which individuals leave unemployment account for most of the changes in unemployment rates in Canada between 1976 and 2008. However, flows into unemployment matter more at some disaggregated levels. There are also some differences in the contributions of flows into and out of unemployment to changes in unemployment rates across the 1981–82 and 1990–92 recessions.     

Trade balance dynamics and exchange rates: In search of the J‐curve using a structural gravity approach

This paper uses a structural gravity approach, specifying currency movements as trade cost component to derive an empirical trade balance model, which incorporates multilateral resistance terms and accounts for the cross‐country variation in the exchange rate pass‐through into import and export prices. The model is estimated using quarterly bilateral trade flows between 47 countries over the period 2010Q1 to 2017Q2, disaggregated into 97 commodity groups. Our results support the existence of an “aggregate” J‐curve, pooled over commodity groups; at the same time they point to considerable heterogeneity in the trade balance dynamics across industries below the surface of aggregate data.     

Products and Productivity*

When firms make decisions about which product to manufacture at a more disaggregated level than observed in the data, measured firm productivity reflects both characteristics of the firm and attributes of the products that are non‐randomly chosen by the firm. This paper develops a model of industry equilibrium in which firms endogenously sort across products and characterizes the resulting bias in measured firm and aggregate productivity. Calibrating the model's parameters, we show that endogenous product selection can have quantitatively important effects on measured firm and aggregate productivity and their response to changes in parameter values.     

Do Multinational Enterprises Contribute to Convergence or Divergence? A Disaggregated Analysis of US FDI*

It is widely held that foreign direct investment (FDI) has a positive effect on economic growth. To test this hypothesis, we perform convergence regressions derived from a theoretical model on the impact of FDI on endogenous technological change in small economies. The model includes FDI externalities that enhance growth, but also shows that FDI can crowd out host country income and reduce local innovation. The empirical analysis employs disaggregated US data for various FDI‐related activities—in addition to the conventionally used aggregate FDI stocks and flows. We estimate the net FDI impact on the convergence rate of per‐capita income to US levels, controlling for human development, financial development, and trade. We find that FDI accelerates convergence for high‐income countries only, otherwise slowing it down.     

Trade liberalization and industrial structure in Spain: An applied general equilibrium analysis

We empirically evaluate the aggregate welfare effects and structural adjustment for the Spanish economy that would follow from trade liberalization with the European Economic Community. Recent theory suggests that the classical gains form more liberal trade relations could be amplified substantially if EEC liberalization permits Spanish industries to realize economies of scale. These effects depend upon the extent of trade creation and trade diversion resulting from preferential liberalization, which in turn depend on the existing patterns of Spanish resource allocation, trade, and comparative advantage. The estimated results are derived from disaggregated microeconomic model of the Spanish economy. We find that increasing returns can actually be beneficial or detrimental, depending upon the interactions between trade and policy toward domestic industry.     

Sectoral Changes in Employment: An eclectic perspective on ‘good’ jobs and ‘poor’ jobs

The linkage Keynes established between the volume of employment that business firms require to make a particular number of jobs available provides an operational perspective about the way in which labor markets work. The aggregate supply or Z function is, in fact, a job offer curve. The most significant insight to derive from this curve is that job offers are inseparable from the economy's aggregate expenditure (or demand) level. This interdependency of aggregate supply and aggregate demand is necessary to understand the functioning of labor markets in the real world. This paper argues that a disaggregated model which encapsulates the economy's price-taking and price-making sectors offers a promising analytical tool to gain perspective about ‘good jobs’ and ‘poor jobs’ in post-Fordist economies. It is maintained that the sectoral deployment of workers reflects whether employing firms, as price-makers, can capture the increasing returns inherent in modern technology.     

The gains and losses to predicting nominal income by disaggregating via the new classical aggregate supply and rational expectations hypotheses

In this paper we compaia the predictive power of two types of model of nominal income: one based on a simple single equation aggregate framework; the second disaggregated into price level and output components. The source of the decomposition of nominal income of the type of model that is considered here are the twin hypotheses of rational expectations and structural neutrality. The model chosen as being representative of this approach to macroeconomic model building and against which some single equation models are compared isBarro's [1978] model of the price level and output in the U.S.     

The Effect of Nominal Demand Shocks on Manufacturing Output: Evidence from Disaggregated Australian Data*

The menu costs model predicts that during times of rapid inflation firms are less likely to vary output in response to changes in nominal aggregate demand. This paper tests the proposition using a disaggregated sample of Australian three-digit ASIC manufacturing industries. The results show that a significant number of Australian industries exhibit behaviour that is consistent with this prediction. In addition, the results show that the variability of inflation and changes to the import penetration ratio also influence the response of output to nominal demand changes.     

Combination forecasts of tourism demand with machine learning models

The main objective of this study is to analyse whether the combination of regional predictions generated with machine learning (ML) models leads to improved forecast accuracy. With this aim, we construct one set of forecasts by estimating models on the aggregate series, another set by using the same models to forecast the individual series prior to aggregation, and then we compare the accuracy of both approaches. We use three ML techniques: support vector regression, Gaussian process regression and neural network models. We use an autoregressive moving average model as a benchmark. We find that ML methods improve their forecasting performance with respect to the benchmark as forecast horizons increase, suggesting the suitability of these techniques for mid- and long-term forecasting. In spite of the fact that the disaggregated approach yields more accurate predictions, the improvement over the benchmark occurs for shorter forecast horizons with the direct approach.     

Aggregate productivity and aggregate technology

Aggregate productivity and aggregate technology are meaningful but distinct concepts. We show that a slightly modified Solow productivity residual measures changes in economic welfare, even when productivity and technology differ because of distortions such as imperfect competition. Our results imply that aggregate data can be used to measure changes in welfare, even when disaggregated data are needed to measure technical change. We then present a general accounting framework that identifies several new non-technological gaps between productivity and technology, gaps reflecting imperfections and frictions in output and factor markets. Empirically, we find that these gaps are important, even though we abstract from variations in factor utilization and estimate only small average sectoral markups. The evidence suggests that the usual focus on one-sector DSGE models misses a rich class of important propagation mechanisms that are present only in multi-sector models.     

A contribution to the empirics of press freedom and corruption

We test the relationship between aggregate press freedom and corruption performing a modified extreme bounds analysis. We also test the relation among different forms of restrictions to press freedom using previously unexplored disaggregated data. Our results support the theoretical view that restrictions to press freedom leads to higher corruption. Furthermore, we obtain that both political and economic influences on the media are strongly and robustly related to corruption, while detrimental laws and regulations influencing the media are not. In all cases the evidence indicates, although not conclusively, that the direction of causation runs from a freer press to lower corruption.     

On the time allocation of married couples since 1960

In the last half a century, married females more than doubled their workforce participation and significantly reduced their time spent on home production. Using a model of family decision making with home production and individual earnings heterogeneity, we subject two prominent explanations for this aggregate change, namely, the evolution of the gender earnings gap and the cost of home appliances, to quantitative tests with respect to changes in participation for disaggregated groups of couples and trends in time spent in leisure and home production activities. We find that both forces are needed to understand the evolution of married female time allocation over time, although the falling cost of home appliances is a dominant explanation for the time allocation outside of workplace, while the gender earnings gap is the dominant explanation for the workforce participation decision.     

Labour market forecasting in Germany: is disaggregation useful?

This paper examines whether labour market forecasts can be improved by using disaggregated information. We construct vector-autoregressive models for employment by sector in order to produce out-of-sample forecasts of aggregate employment. Forecast accuracy is compared to univariate models by using Clark/West tests. In an application to German data, it is evident that disaggregation significantly improves the employment forecast. Moreover, using fluctuation-window tests we find that disaggregation yields superior results especially in phases with strong and sustained employment changes.     

Wage and unemployment: Evidence from online job vacancy data

This paper examines the relationship between labour market conditions and wage dynamics by exploiting a unique dataset of more than one million online job vacancies. We find a weak trade-off between aggregate wage inflation and unemployment. This link becomes more evident when the wage inflation is disaggregated at the sectoral and occupational level. The examination, using vacancy-level data, shows a negative correlation between offered wage and unemployment. The degree of wage elasticity, however, is different across regions and skill segments. Our findings suggest the importance of micro-level data's unique dimensions in examining the wage – unemployment relationship.     

Do disaggregated CPI data improve the accuracy of inflation forecasts?

In this paper, we evaluate the role of using consumer price index (CPI) disaggregated data to improve the accuracy of inflation forecasts. Our forecasting approach is based on extracting the factors from the subcomponents of the CPI at the highest degree of disaggregation. The data set contains 54 macroeconomic series and 243 CPI subcomponents from 1992 to 2009 for Mexico. We find that the factor models that include disaggregated data outperform the benchmark autoregressive model and the factor models containing alternative groups of macroeconomic variables. We provide evidence that using disaggregated price data improves forecasting performance. The forecasts of the factor models that extract the information from the CPI disaggregated data are as accurate as the forecasts from the survey of experts.