Showing papers by "Bart Hobijn published in 2004"

Generalizations of the KPSS-test for stationarity

Abstract: We propose automatic generalizations of the KPSS-test for the null hypothesis of stationarity of a univariate time series. We can use these tests for the null hypotheses of trend stationarity, level stationarity and zero mean stationarity. We introduce the asymptotic null distributions and we determine consistency against relevant nonstationary alternatives. We compare the properties of the tests with those of other proposed tests for stationarity. Monte Carlo simulations support the relevance of the tests when an autoregressive process with large positive autocorrelations is likely under the null hypothesis.

Menu costs at work: restaurant prices and the introduction of the euro

Abstract: Restaurant prices in the euro area saw an unprecedented increase after the introduction of the euro. We use an extension of commonly used models of sticky prices and argue that the increase in restaurant prices can be explained by menu costs. The extension we use involves the state-dependent decision of firms about when to adopt the euro. Two main mechanisms drive the result. First, our model concentrates otherwise staggered price increases around the introduction of the euro. Second, before the adoption of the euro, prices do not reflect marginal cost increases expected to occur after the changeover. This horizon effect disappears as soon as the new currency is adopted, contributing to a jump in prices at that time. For realistic parameter values, the model generates a blip in inflation of the same magnitude observed in the data.

Neoclassical Growth and the Adoption of Technologies

Abstract: We introduce a growth model of technology diffusion and endogenous Total Factor Productivity (TFP) levels both at the sector and aggregate level At the aggregate, the model behaves as the Neoclassical growth model Our goal is for this model to bridge the gap between the theoretical and empirical studies of technology adoption and economic growth We bridge this gap in three important directions First of all, we use our model to show how one unified theoretical framework is broadly consistent with the observed dynamics of both economic growth as well as of many different measures of technology adoption, like adoption rates, capital to output ratios, and output ratios Secondly, we estimate our model using a broad range of technological adoption measures, covering 17 technologies and 21 industrialized countries over the past 180 years This allows us to show how its predicted adoption patterns fit those observed in the data Finally, we estimate the disparities in sectoral productivity levels as well as aggregate TFP that can be attributed to the differences in the range of technologies in use across countries These disparities are almost completely determined by the quality of the worst technology in use, rather than by the quality of the newest technology that has just been adopted or by the number of technologies in use Further, we find that the TFP component attributable to the range of technologies used is highly correlated with overall sectoral TFP differences across countries, though the variance is smaller

Neoclassical Growth and the Adoption of Technologies

Abstract: We introduce a growth model of technology diffusion and endogenous Total Factor Productivity (TFP) levels both at the sector and aggregate level. At the aggregate, the model behaves as the Neoclassical growth model. Our goal is for this model to bridge the gap between the theoretical and empirical studies of technology adoption and economic growth. We bridge this gap in three important directions. First of all, we use our model to show how one unified theoretical framework is broadly consistent with the observed dynamics of both economic growth as well as of many different measures of technology adoption, like adoption rates, capital to output ratios, and output ratios. Secondly, we estimate our model using a broad range of technological adoption measures, covering 17 technologies and 21 industrialized countries over the past 180 years. This allows us to show how its predicted adoption patterns fit those observed in the data. Finally, we estimate the disparities in sectoral productivity levels as well as aggregate TFP that can be attributed to the differences in the range of technologies in use across countries. These disparities are almost completely determined by the quality of the worst technology in use, rather than by the quality of the newest technology that has just been adopted or by the number of technologies in use. Further, we find that the TFP component attributable to the range of technologies used is highly correlated with overall sectoral TFP differences across countries, though the variance is smaller.

Menu Costs at Work: Restaurant Prices and the Introduction of the Euro

Abstract: Restaurant prices in the euro area saw an unprecedented increase after the introduction of the euro. We use an extension of commonly used models of sticky prices and argue that the increase in restaurant prices can be explained by menu costs. The extension we use involves the state-dependent decision of firms about when to adopt the euro. Two main mechanisms drive the result. First, our model concentrates otherwise staggered price increases around the introduction of the euro. Second, before the adoption of the euro, prices do not reflect marginal cost increases expected to occur after the changeover. This horizon effect disappears as soon as the new currency is adopted, contributing to a jump in prices at that time. For realistic parameter values, the model generates a blip in inflation of the same magnitude observed in the data.

Lobbying and Technology Diffusion

Abstract: Do lobbies affect technology diffusion and growth? A number of authors have identified the importance of vested interests as a deterrent to technology diffusion and the relevance that this may have for growth. however, the evidence that exists about this mechanism is just anecdotal. In this paper we build a model of lobbying and technology diffusion where the speed of diffusion of new technologies depends on some dimensions of the political regime and on the whether there is an old technology that may be substituted by the new technology. This differential effect of institutions on the diffusion of technologies with a predecessor constitutes the central element of our identification strategy. To implement this test we use technology diffusion data from Comin and Hobijn [2004]. We find that the relevant institutional variables have a differential effect on the diffusion of technologies with a predecessor technology as predicted by the theory. We show that this result is unlikely to be driven by omitted variables, or reverse causality.