Measuring TFP: A Latent Variable Approach

Despite the important role that total factor productivity (TFP) has played in growth literature, few attempts have been made to change the methodology to estimate it. This paper proposes a methodology based on state–space model to estimate TFP and its determinants. With this methodology it is possible to reduce the measurement of our ignorance. As a by-product, this estimation yields the capital share in output and the long-term growth rate. When applied to Chile, the estimation shows a capital share around 0.5 and long term growth of TFP around 1%. Capital accumulation tends to explain more the growth rate in the fast growth periods under the econometric estimation compared to the traditional growth accounting methodology. l II) could be helpful on this task.

Macroeconomic Consequences of Ageing and Directed Technological Change. BertelsmannStiftung Studies

Macroeconomic Consequences of Ageing and Directed Technological Change Demographic projections foresee a pronounced population ageing process in the coming decades. The associated changes in quantity and quality of labour will have an impact on the long-term economic outlook. This study discusses economic implications of current demographic projections for a set of large industrialized economies, which include the largest member states of the EU, the USA and Japan, as well as Austria as an example of a small open economy. The focus of the study is the interplay between demographic and technological trends. The study extends the methodology of the European Commission’s Ageing Report by considering the effects of size and composition of the working-age population on the productivity growth and productivity effect of the ICT-intensity as a measure of directed technological change

Fiscal Policy and Macroeconomic Uncertainty in Developing Countries: The Tale of the Tormented Insurer

Governments in emerging markets often behave like a "tormented insurer," trying to use non-state-contingent debt instruments to avoid cuts in payments to private agents despite large fluctuations in public revenues. In the data, average public debt-GDP ratios decline as the variability of revenues increases, primary balances and current expenditures follow cyclical patterns sharply at odds with the countercyclical patterns of industrial countries, and the cyclical variability of public expenditures exceeds that of private expenditures by a wide margin. This paper proposes a model of a small open economy with incomplete markets that can rationalize this behavior. In the model a fiscal authority makes optimal expenditure and debt plans given shocks to output and revenues, and private agents make optimal consumption and asset accumulation plans. Quantitative analysis of the model calibrated to Mexico yields a negative relationship between average public debt and revenue variability similar to the one observed in the data. The model mimics Mexico's GDP correlations of government purchases and the primary balance. The ratio of public-to-private expenditures fluctuates widely and the implied welfare costs dwarf conventional estimates of negligible benefits of risk sharing and consumption smoothing.

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed

Estimating Gaps and Trends for the Chilean Economy

Trend GDP and the output gap are key inputs for policy evaluation and forecasting in standard models of monetary policy. However, the measurement of these variables is plagued with difficulties. In this paper we propose two different approaches. First, a data-based approach, that starts with the primal and dual estimates of total factor productivity (TFP) growth, and then uses a variety of procedures to filter the inputs. Second, a model-consistent framework that simultaneously estimates the macroeconomic dynamics and the underlying trends of the economy. We compare the difficulties in using each methodology, and we use them to construct measures of the output gap and potential growth for Chile

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed.business cycle; continuous time econometrics; investment cycle; inventory cycle; maximum entropy spectral analysis; parametric resonance

Investment shocks and business cycles

Shocks to the marginal efficiency of investment are the most important drivers of business cycle fluctuations in US output and hours. Moreover, these disturbances drive prices higher in expansions, like a textbook demand shock. We reach these conclusions by estimating a DSGE model with several shocks and frictions. We also find that neutral technology shocks are not negligible, but their share in the variance of output is only around 25 percent, and even lower for hours. Labor supply shocks explain a large fraction of the variation of hours at very low frequencies, but not over the business cycle. Finally, we show that imperfect competition and, to a lesser extent, technological frictions are the key to the transmission of investment shocks in the model.Investments ; Business cycles

Testing a DSGE model and its partner database

There is now an impetus to apply dynamic stochastic general equilibrium models to forecasting. But these models typically rely on purpose-built data, for example on tradable and nontradable sector outputs. How then do we know that the model will forecast well, in advance? We develop an early warning test of the database-model match and apply that to a Colombian model. Our test reveals where the combination should work (consumption) and where not (in investment). The test can be adapted to look at many likely sources of DSGE model failure.Monetary Policy, Sectoral Model, DSGE, Forecast Performance, Kalman Filter. Classification JEL: F47; E01; C61

DSGE Models in a Data-Rich Environment

Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However, recent empirical research on factor models has shown that information contained in large data sets is relevant for the evolution of important macroeconomic series. This suggests that conventional model estimates and inference based on estimated DSGE models might be distorted. In this paper, we propose an empirical framework for the estimation of DSGE models that exploits the relevant information from a data-rich environment. This framework provides an interpretation of all information contained in a large data set, and in particular of the latent factors, through the lenses of a DSGE model. The estimation involves Markov-Chain Monte-Carlo (MCMC) methods. We apply this estimation approach to a state-of-the-art DSGE monetary model. We find evidence of imperfect measurement of the model's theoretical concepts, in particular for inflation. We show that exploiting more information is important for accurate estimation of the model's concepts and shocks, and that it implies different conclusions about key structural parameters and the sources of economic fluctuations.