Employment responses to aggregate and sectoral technology shocks

This paper investigates the responses of sectoral employment in US manufacturing to a technology shock by its type: aggregate or sectoral. In order to distinguish between aggregate and sectoral shocks, we construct independent VAR models for identifying each shock separately: a factor-augmented vector autoregression (FAVAR) for aggregate shocks and a sectoral SVAR for sectoral shocks. Our aggregate model in particular extends the conventional small-scale VAR to the FAVAR framework of Bernanke et al. (2005) so that it can address the potential bias from omitted variables. The main findings are as follows: most industries exhibit negative employment responses to an aggregate technology shock while exhibiting positive responses to a sectoral technology shock. By comparing our FAVAR framework with Chang and Hong’s (2006) small-scale VAR, we show that applying the FAVAR results in significant differences in the estimated responses to an aggregate technology shock. Real rigidities (such as slow diffusion of new technology or frictional labor reallocation), rather than nominal rigidities (such as sticky prices), are crucial in accounting for the cross-industry difference in employment responses. In particular, the slow diffusion of new technology is closely related to the sluggish response of sectoral employment.     

The cyclical behavior of job creation and job destruction: A sectoral model

Summary Three key features of the employment process in the U.S. economy are that job creation is procyclical, job destruction is countercyclical, and job creation is less volatile than job destruction. These features are also found at the sectoral (goods and services) level. The paper develops, calibrates and simulates a two-sector general equilibrium model that includes both aggregate and sectoral shocks. The behavior of the model economy mimics the job creation and destruction facts. A non-negligible amount of unemployment arises due to the presence of aggregate and sectoral shocks.We thank Jeffrey Campbell, Richard Rogerson and two referees for helpful comments. We are grateful to M.J.D. Powell for providing us with his GETMIN FORTRAN subroutine.     

Sectoral and Aggregate Technology Shocks:Is There a Relationship?

We analyze sector-specific shocks in productivity and demand in 19 manufacturing sectors of the Austrian economy. Based on a structural vector autoregressive model (SVAR) with long-run restrictions developed by Galí (1999) we extract technology and non-technology shocks from sectoral and aggregate data. We study their patterns and relationship by means of a principal components analysis and find a close association of sectoral and macroeconomic non-technology shocks but only a very weak association for technology shocks. Impulse response analysis indicates that for almost all manufacturing sectors as well as the aggregate Austrian economy productivity growth rates experience an immediate increase due to positive technology shocks while hours worked decline. Thereby we confirm Galís results on the level of Austrian manufacturing industries. From regression analysis, we find that our shocks are closely associated to employment growth and output growth but not to investment growth and that the reaction is different for the aggregate economy and manufacturing industries.JEL codes: D24, E23, E32, O30We thank Werner Müller and the participants of the 2004 conference of the Austrian Economic Association (NOeG) for helpful comments. We would like to thank an anonymous referee for many helpful comments that led to a substantial improvement of the paper. The usual disclaimer applies. This research project was supported by a research Grant (Project Nr. 9800) of the Jubiläumsfonds der Österreichische Nationalbank (OeNB).     

Micro vs macro explanations of post-war US unemployment movements

This paper considers contributions of industry-sectoral-micro shocks vs aggregate macro shocks. A dynamic factor model is estimated with maximum likelihood method in the frequency domain, and decomposes US unemployment movements into industry sectoral and common components. Sectoral shocks account for around half unemployment movements.     

The impact of productivity and demand shocks on structural dynamics: Evidence from Austrian manufacturing

Based on Pasinetti's model of structural dynamics we develop an empirical identification strategy for aggregate and sectoral labor productivity and demand shocks in a structural vector autoregressive model with long-run restrictions. Impulse response analysis shows that we can distinguish four patterns of the effects of changes in demand and productivity growth on sectoral output growth. For some industries demand is indeed the factor driving sectoral growth. Labor productivity and demand shocks are closely associated with the growth rates of employment and output across industries. However, there is less correlation with entry and exit. This suggest that structural change within and between industries may have quite different determinants.     

Wage-setting coordination in a small open economy*

This paper studies wage-setting coordination in a two-sector, open economy dynamic stochastic general equilibrium model. Two large sectoral unions anticipate the effects of their wage demands on aggregate variables. In an open economy, there are externalities that the unions can take into account to increase aggregate welfare, but the strategic interaction between the sectoral unions tends to erode this gain. When wage coordination takes place through a wage norm set by either of the sectors, this minimizes the strategic interaction. However, wage norms create welfare losses as sector-specific wage adjustment is required to make an efficient adjustment to shocks.     

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.     

Lost in transition: the costs and consequences of sectoral labour adjustment

Abstract This paper uses an equilibrium search and matching model to study Canada’s sectoral labour adjustment in 2002–2006 during an increase in global commodity prices and exchange rate appreciation. I estimate economically significant adjustment costs for the aggregate economy in this episode and demonstrate that difficulty in transferring skills between jobs for individual workers can be an important contributor to these aggregate costs. The analysis also demonstrates that the level of unemployment benefits impacts the economy’s sectoral composition, its aggregate productivity, and the speed of its adjustment to shocks.     

Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics

This paper develops a method for analysing the dynamics of large cross-sections based on a factor analytic model. We use "law of large numbers" arguments to show that the number of common factors can be determined by a principal components method, the economy-wide shocks can be identified by means of simple structural VAR techniques and that the parameters of the unobserved factor model can be estimated consistently by applying OLS equation by equation. We distinguish between a technological and a non-technological shock. Identification is obtained by minimizing the negative realizations of the technology shock. Empirical results on 4-digit industrial output and productivity for the U.S. economy from 1958 to 1986 show that: (1) at least two economy-wide shocks, both having a long-run effect on sectoral output, are needed to explain the common dynamics; (2) although the technological shock accounts for at least 50 per cent of the aggregate dynamics of output, it cannot by itself explain dynamics at business cycle frequencies; (3) sector-specific shocks explain the main bulk of total variance but generate mainly high frequency dynamics; (4) both the technological and the non-technological component of output show a peak for positive sectoral comovements of output at business cycle frequencies; (5) technological shocks are strongly correlated with the growth rates of the investment in machinery and equipment sectors and their inputs.     

Sectoral shocks and business cycles: a disaggregated analysis of output fluctuations in the UK

In this paper we first show that it is possible to modify linear real business cycle models to allow for disaggregate (industry-specific) factors in the generation of macroeconomic fluctuations. We then try to determine the relative importance of aggregate and sectoral shocks by doing principal components analysis on the residuals from a VAR of output growth rates in 19 UK industrial sectors. We find that a significant percentage of the innovations in sectoral output growths can be accounted for by a single unobserved component. However, since the model only sets an upper bound to the explanatory power of aggregate impulses, the importance of using sectoral data to extract additional information to bear on the analysis of economic fluctuations is confirmed by our findings.     

Do technology shocks lower hours worked? – Evidence from Japanese industry level data

We examine the response of productivity and hours worked to technology and nontechnology shocks using the Japan Industrial Productivity (JIP) Database. We find that, at the aggregate level, positive technology shocks increase hours worked both in the manufacturing and the nonmanufacturing sector, accounting for a large fraction in the variances of hours worked. At the two- and three-digit industry levels, in contrast, we find that the correlation between productivity and hours worked in response to sectoral technology shocks tends to be negative. Further, we find that neither aggregate nor sectoral technology shocks appear to be the dominant factor underlying fluctuations in hours worked at the disaggregate level. The productivity decline in response to nontechnology shocks is not related to a permanent change in the relative size of industries.     

Market institutions,labor market dynamics,and productivity in Argentina during the 1990s

This paper addresses the effects of policy shocks and structural reforms on the dynamic behavior of manufacturing job flows and productivity in Argentina during the 1990s, and the contribution of job reallocation to productivity. The main findings are: (a) shocks to labor taxes have allocative effects, while financial shocks have aggregate effects; (b) import tariffs appear to protect obsolete jobs; (c) sectoral differences in labor intensity, openness, financial dependence and workers’ strength shape the responses to shocks; (d) intra‐ and inter‐sectoral reallocations contribute positively to productivity; and (e) trade liberalization and labor market flexibilization favor reallocation and creative destruction.     

Productivity propagation with networks transformation

We model sectoral production by cascading binary compounding processes. The sequence of processes is discovered in a self-similar hierarchical structure stylized in the economy-wide networks of production. All substitution elasticities and Hicks-neutral productivity growth are calibrated so that the general equilibrium feedbacks between all sectoral unit cost functions replicate the transformation of networks observed as a set of two temporally distant input-output coefficient matrices. This system of unit cost functions is then examined to study how idiosyncratic sectoral productivity shocks propagate into aggregate macroeconomic fluctuations in light of potential networks transformation. Additionally, we study how sectoral productivity increments propagate into the dynamic general equilibrium, thereby allowing networks transformation and ultimately producing social benefits.     

Cyclicality and Sectoral Linkages: Aggregate Fluctuations from Independent Sectoral Shocks

The traditional argument against the relevance of sector-specific shocks for the aggregate phenomenon of business cycles invokes the law of large numbers: positive shocks in some sectors are offset by negative shocks in other sectors. This paper hypothesizes that cancellation of sector-specific shocks via the law of large numbers is affected by interactions among producing sectors. The analysis is performed within the context of a multisector model similar in spirit to that of Long and Plosser [J. Polit. Econ.91(1983), 39–69]. It is shown that the rate at which the law of large numbers applies is controlled by the rate of increase in the number offullrows in the input-use matrix rather than by the rate of increase in the total number of sectors. Investigations of actual input-use matrices from the U.S. economy reveal that the number of full rows increases much slower than the total number of rows upon disaggregation, and when these input-use matrices are used to parameterize the model, aggregate volatility from sectoral shocks declines at less than half the rate implied by the law of large numbers. This finding leaves open the possibility that a sizeable portion of aggregate volatility is caused by “smaller” shocks to individual sectors. Simple statistics calculated from the model indicate that as much as 80% the volatility in U.S. gross domestic product growth rates could be the result of independent shocks to two-digit Standard Industrial Code sectors.Journal of Economic LiteratureClassification Numbers: E1, E32, C67.     

The Impact of Euro on Sectoral Equity Returns and Portfolio Risk

This paper examines the implications of the adoption of the euro and the resulting monetary policy integration for investors in the Euro area in terms of stock market diversification. In particular, we study the difference between investment strategies based on country indices and on sector indices. In addition, we use GARCH-M to model return and volatility for the daily sectoral euro equity indices from 1992 to 2009 to analyze how and to what extent volatility in the sector equity index is driven by shocks occurring in the US, aggregate European equity index, aggregate Euro Zone equity index, and the global equity index. We find strong evidence that diversification over sectors yields more efficient portfolios than diversification over countries and that the volatility spillover of the aggregated Euro zone equity return index on the sectoral equity return index has increased after the launch of the euro.     

THE TRANSMISSION OF MONETARY POLICY IN A MULTISECTOR ECONOMY*

This article constructs and estimates a sticky‐price, Dynamic Stochastic General Equilibrium model with heterogeneous production sectors. Firms in different sectors vary in their price rigidity, production technology, and the combination of material and investment inputs. In particular, firms buy inputs from all sectors using the actual Input–Output Matrix and Capital Flow Table of the U.S. economy. By relaxing the standard assumption of symmetry, this model allows idiosyncratic sectoral dynamics in response to monetary policy shocks. The model is estimated by the Generalized Method of Moments using sectoral and aggregate U.S. time series.     

Sticky prices or rational inattention – What can we learn from sectoral price data?

This paper derives stylised facts on sectoral inflation dynamics and confronts these facts with two popular theoretical models of price setting. Based on sectoral price responses to macroeconomic shocks estimated from an approximate factor model, we find that the frequency of price changes explains a relevant share of the cross-sectional variation of the speed and size of responses. Moreover, there is little evidence that the volatility of sectoral inflation due to idiosyncratic shocks dampens the size and speed of the responses to macroeconomic shocks. These findings support a multi-sector model with sticky prices rather than a rational-inattention model. We derive the results from different modelling and sampling decisions proposed in the literature, and we find that the explanatory power of the frequency of price changes for the speed of response to a macroeconomic shock proves robust in the face of these decisions. Other results are sensitive with respect to the choice of the factor model and the treatment of outliers.     

Diversification across ASEAN-wide sectoral and national equity returns

This paper examines the effects of local and global shocks on the sector indices and national returns of the Association of Southeast Asian Nations (ASEAN) by using the univariate AR-GARCH model. We find that regional and global shocks have different influences on the ASEAN-wide sector and national equity indices. There is evidence that the ASEAN-wide sectoral returns are mostly driven by local shocks, except for the insurance and technology sectors. The volatility of Singapore's and Vietnam's national returns mostly results from their own shocks rather than local and global shocks. Applying the trend spillover model, this paper also shows that the effects of regional and global shocks on return volatility have been decreasing for almost all ASEAN-wide sectors' equity indices, while the trend for the volatility spillover effects of those shocks are positive and significant for the production and industries group sectors, as well as the food and beverage sector. Comparing the variance ratios of ASEAN sectoral and national returns, it is evident that the percentage of national equity returns belonging to their own shocks is higher than that of sectoral returns, indicating that investors might be better off diversifying their assets across countries rather than sectors in ASEAN area. This finding is consistent with the results of the mean–variance frontiers, as the portfolio composed purely of ASEAN national returns has a stronger efficiency frontier than a portfolio of all ASEAN-wide sector equity returns. By using the spanning and intersection tests, the paper also indicates that adding ASEAN national equity returns might improve the efficiency frontiers of investors' holding portfolios.     

What broad banks do, and markets don’t: Cross-subsidization

We show that interbank markets are a poor substitute for “broad” banks that operate across regions or sectors. In the presence of regional or sectoral asset and liquidity shocks, interbank markets can distribute liquidity efficiently, but fail to respond efficiently to asset shocks. Broad banks can condition on the joint distribution of both shocks and, hence, achieve an efficient internal allocation of capital. This allocation involves the cross-subsidization of loans across regions or sectors. Compared to regional banks that are linked through well-functioning interbank markets, broad banks lead to higher levels of aggregate investment, higher output, and less fluctuations within regions. However, broad banks generate endogenously aggregate uncertainty.     

Employment and wages with sector-specific shocks and worker moral hazard

We study a model of worker moral hazard with identical workers and where sectoral prices are subject to stochastic shocks. When firms are short-run maximizers, employment is shown to be distorted downward relative to the case of certain prices, and more so the higher is the current price. This implies that employment is relatively insensitive to sectoral output-price changes, and that average employment and output are reduced when price volatility increases. When firms can commit to future employment levels, employment is greater in low-demand states (implying labor hoarding), and thus even less sensitive to shocks, while average employment is less distorted downward by uncertainty. The model gives a new explanation of how increased sector-specific volatility can lead to output losses, and of the possibility of negative comovements of unemployment and turnover.