Bridging DSGE models and the raw data

A method to estimate DSGE models using the raw data is proposed. The approachlinks the observables to the model counterparts via a flexible specification which doesnot require the model-based component to be solely located at business cycle frequencies,allows the non model-based component to take various time series patterns, andpermits model misspecification. Applying standard data transformations induce biasesin structural estimates and distortions in the policy conclusions. The proposed approachrecovers important model-based features in selected experimental designs. Twowidely discussed issues are used to illustrate its practical use.

Business cycle measurement with some theory

A method to evaluate cyclical models not requiring knowledge of the DGP and the exact specificationof the aggregate decision rules is proposed. We derive robust restrictions in a class of models; use someto identify structural shocks in the data and others to evaluate the class or contrast sub-models. Theapproach has good properties, even in small samples, and when the class of models is misspecified. Themethod is used to sort out the relevance of a certain friction (the presence of rule-of-thumb consumers)in a standard class of models.

Geographical effects on the accuracy of textile trade data:an international approach for 1913

Foreign trade statistics are the main data source to the study of international trade.However its accuracy has been under suspicion since Morgernstern published hisfamous work in 1963. Federico and Tena (1991) have resumed the question arguing thatthey can be useful in an adequate level of aggregation. But the geographical assignmentproblem remains unsolved. This article focuses on the spatial variable through theanalysis of the reliability of textile international data for 1913. A geographical biasarises between export and import series, but because of its quantitative importance it canbe negligible in an international scale.

Relative price riddles in international business cycle theory: Are transport costs the explanation?

We study relative price behavior in an international business cyclemodel with specialization in production, in which a goods marketfriction is introduced through transport costs. The transporttechnology allows for flexible transport costs. We analyze whetherthis extension can account for the striking differences betweentheory and data as far as the moments of terms of trade and realexchange rates are concerned. We find that transport costs increaseboth the volatility of the terms of trade and the volatility of thereal exchange rate. However, unless the transport technology isspecified by a Leontief technology, transport costs do not resolvethe quantitative discrepancies between theory and data. Asurprising result is that transport costs may actually lower thepersistence of the real exchange rate, a finding that is in contrastto much of the emphasis of the empirical literature.

Disability, capacity for work and the business cycle: An international perspective

An important policy issue in recent years concerns the number of people claimingdisability benefits for reasons of incapacity for work. We distinguish between workdisability , which may have its roots in economic and social circumstances, and healthdisability which arises from clear diagnosed medical conditions. Although there is a linkbetween work and health disability, economic conditions, and in particular the businesscycle and variations in the risk of unemployment over time and across localities, mayplay an important part in explaining both the stock of disability benefit claimants andinflows to and outflow from that stock. We employ a variety of cross?country andcountry?specific household panel data sets, as well as administrative data, to testwhether disability benefit claims rise when unemployment is higher, and also toinvestigate the impact of unemployment rates on flows on and off the benefit rolls. Wefind strong evidence that local variations in unemployment have an importantexplanatory role for disability benefit receipt, with higher total enrolments, loweroutflows from rolls and, often, higher inflows into disability rolls in regions and periodsof above?average unemployment. Although general subjective measures of selfreporteddisability and longstanding illness are also positively associated withunemployment rates, inclusion of self?reported health measures does not eliminate thestatistical relationship between unemployment rates and disability benefit receipt;indeed including general measures of health often strengthens that underlyingrelationship. Intriguingly, we also find some evidence from the United Kingdom and theUnited States that the prevalence of self?reported objective specific indicators ofdisability are often pro?cyclical that is, the incidence of specific forms of disability arepro?cyclical whereas claims for disability benefits given specific health conditions arecounter?cyclical. Overall, the analysis suggests that, for a range of countries and datasets, levels of claims for disability benefits are not simply related to changes in theincidence of health disability in the population and are strongly influenced by prevailingeconomic conditions. We discuss the policy implications of these various findings.

Hybrid consumption paths in the attribute space: A model and application with scanner data

This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.

Causes of subcontracting: Evidence from panel data on construction firms

This paper examines factors explaining subcontracting decisions in the construction industry. Rather than the more common cross-sectional analyses, we use panel data to evaluate the influence of all relevant variables. We design and use a new index of the closeness to small numbers situations to estimate the extent of hold-up problems. Results show that as specificity grows, firms tend to subcontract less. The opposite happens when output heterogeneity and the use of intangible assets and capabilities increase. Neither temporary shortage of capacity nor geographical dispersion of activities seem to affect the extent of subcontracting. Finally, proxies for uncertainty do not show any clear effect.

Endogenous labor market participation and the business cycle

Existing models of equilibrium unemployment with endogenous labor market participation are complex, generate procyclical unemployment rates and cannot match unemployment variability relative to GDP. We embed endogenous participation in a simple, tractable job market matching model, show analytically how variations in the participation rate are driven by the cross-sectional density of home productivity near the participation threshold, andhow this density translates into an extensive-margin labor supply elasticity. A calibration of the model to macro data not only matches employment and participation variabilities but also generates strongly countercyclical unemployment rates. With some wage rigidity the model also matches unemployment variations well. Furthermore, the labor supply elasticity implied by our calibration is consistent with microeconometric evidence for the US.

Comparative advantage and the cross-section of business cycles

Business cycles are both less volatile and more synchronized with the world cycle in rich countries than in poor ones. We develop two alternative explanations based on the idea that comparative advantage causes rich countries to specialize in industries that use new technologies operated by skilled workers, while poor countries specialize in industries that use traditional technologies operated by unskilled workers. Since new technologies are difficult to imitate, the industries of rich countries enjoy more market power and face more inelastic product demands than those of poor countries. Since skilled workers are less likely to exit employment as a result of changes in economic conditions, industries in rich countries face more inelastic labour supplies than those of poor countries. We show that either asymmetry in industry characteristics can generate cross-country differences in business cycles that resemble those we observe in the data.

Do institutional changes affect business cycles? Evidence from Europe

We study the effects that the Maastricht treaty, the creation of the ECB, andthe Euro changeover had on the dynamics of European business cycles using a panelVAR and data from ten European countries - seven from the Euro area and threeoutside of it. There are changes in the features of European business cycles and in thetransmission of shocks. They precede the three events of interest and are more linkedto a general process of European convergence and synchronization.

The statistical accuracy of surveys on business and economic perspectives: a case study

In this paper, we develop a new decision making model and apply it in political Surveys of economic climate collect opinions of managers about the short-term future evolution of their business. Interviews are carried out on a regular basis and responses measure optimistic, neutral or pessimistic views about the economic perspectives. We propose a method to evaluate the sampling error of the average opinion derived from a particular type of survey data. Our variance estimate is useful to interpret historical trends and to decide whether changes in the index from one period to another are due to a structural change or whether ups and downs can be attributed to sampling randomness. An illustration using real data from a survey of business managers opinions is discussed.

Man-bites-dog business cycles

The newsworthiness of an event is partly determined by how unusual it isand this paper investigates the business cycle implications of this fact. In particular, weanalyze the consequences of information structures in which some types of signals are morelikely to be observed after unusual events. Such signals may increase both uncertainty anddisagreement among agents and when embedded in a simple business cycle model, can helpus understand why we observe (i) occasional large changes in macro economic aggregatevariables without a correspondingly large change in underlying fundamentals (ii) persistentperiods of high macroeconomic volatility and (iii) a positive correlation between absolutechanges in macro variables and the cross-sectional dispersion of expectations as measuredby survey data. These results are consequences of optimal updating by agents when theavailability of some signals is positively correlated with tail-events. The model is estimatedby likelihood based methods using individual survey responses and a quarterly time seriesof total factor productivity along with standard aggregate time series. The estimated modelsuggests that there have been episodes in recent US history when the impact on outputof innovations to productivity of a given magnitude was more than eight times as largecompared to other times.

Ambient intelligence application based on environmental measurements performed with an assistant mobile robot

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

Semantic Web applications: a framework for industry and business exploitation – What is needed for the adoption of the Semantic Web from the market and industry

In recent years, Semantic Web (SW) research has resulted in significant outcomes. Various industries have adopted SW technologies, while the ‘deep web’ is still pursuing the critical transformation point, in which the majority of data found on the deep web will be exploited through SW value layers. In this article we analyse the SW applications from a ‘market’ perspective. We are setting the key requirements for real-world information systems that are SW-enabled and we discuss the major difficulties for the SW uptake that has been delayed. This article contributes to the literature of SW and knowledge management providing a context for discourse towards best practices on SW-based information systems.

The Significance of Business Exit for Future Entrepreneurial Activity

Purpose: The purpose of this paper is to analyse the impact of business exits on future dimensions of entrepreneurial activity at the macroeconomic level. Design/methodology/approach: This research uses the Global Entrepreneurship Monitor (GEM) data for 41 countries and the Generalized Method of Moments (GMM) to carry out the analysis. The paper differentiates the effect of the two components of total entrepreneurial activity, and the two motivations for it – opportunity and necessity entrepreneurship. Findings: The results presented here show a positive and significant effect of the coefficient associated with exits in all models. This means that the levels of entrepreneurial activity exceed business exits. The robustness of the models are tested, including other variables such as the fear of failure, the Gross Domestic Product, role models, entrepreneurial skills and the unemployment variables. The main hypothesis which stated that at national level business exits imply greater rates of opportunity-driven entrepreneurship is corroborated. Originality/value: One would expect that unemployment rates would imply higher levels of necessity entrepreneurship. However, results show that unemployment rates do in fact favour opportunity entrepreneurship levels. This could be due to those government policies that are aimed at promoting entrepreneurship through the capitalization of unemployment to be totally invested in a new start-up. To the best of our knowledge, this is the first panel data study to link previous exit rates to future dimensions of entrepreneurial activity. Keywords: Entrepreneurship, business exits, social values, industrial organization Paper type: Research paper