The paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real business cycle model. In particular, we identify from the literature six different hypotheses that generate the empirically observed decline in worked hours after a positive technology shock. These models alternatively exhibit (i) sticky prices; (ii) firm entry and exit with time to build; (iii) habit in consumption and costly adjustment of investment; (iv) persistence in the permanent technology shocks; (v) labor market friction with procyclical hiring costs; and (vi) Leontief production function with labor-saving technology shocks. In terms of model posterior probabilities, impulse responses, and autocorrelations, the model favored is the one that exhibits habit formation in consumption and investment adjustment costs. A robustness test shows that the sticky price model becomes as competitive as the habit formation and costly adjustment of investment model when sticky wages are included.
This paper extends Grossman and Helpman’s seminal work (1991), and presents an endogenous growth model where innovations created in a high-tech sector may be assimilated or adapted by a low-tech sector. Applying a simple Heckscher-Ohlin framework, the effects of technological diffusion are found to allow a country relatively scarce in human capital to benefit from nondecreasing rates of growth through its low-tech sector. The model is tested by using a dynamic panel data approach (Arellano and Bover, 1995). Results are consistent with the predictions of the model and robust to a broad range of definitions of technological intensity.
Evidence from historical and epidemiological literatures show that epidemics tend to spread in the population according to a logistic pattern. We conjecture that the impact of new technologies on output follows a pattern of spread not unlike that of typical epidemics. After reaching a critical mass, rates of growth will accelerate until the marginal benefits of technology are fully utilized. We estimate spline functions using a GMM dynamic panel methodology for 79 countries. We use imports of machinery and equipment as a fraction of gross domestic product as a proxy for the process of technological adoption. Results confirm our hypothesis.
This paper examines the extent to which a dynamic international general equilibrium model can account for observed movements in real interest rates and interest rate differentials. Using data for Group of Seven, the study finds that measured real interest rates are countercyclical in a single country and that the contemporaneous cross-correlations between international real interest differentials and output growth spreads are negative. Predictions of the baseline model are, however, inconsistent with the data. Extending the benchmark model to include habit persistence in consumption improves the match between theory and data.