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time. The first key element of our theory is that energy intensity is a feature of technology and is embodied in capital as a fixed requirement. Capital is putty-clay as in Atkeson and Kehoe (1999) : once the requirement is fixed it cannot be changed over the lifetime of capital. Agents, though, can choose to invest in less (or more) energy intensive capital and that choice responds to economic conditions. The second key element in our theory is that we assume that there is Investment Specific Technical Change (ISTC hereafter). That is, there are innovations that

quality of these investment goods. The distinction between TFP (neutral progress in this paper) and investment-specific technical change (henceforth, ISTC) has been widely used, e.g., Greenwood, Hercowitz, and Krusell (2000) or Fisher (2006), while the one between technical change in non-ICT and ICT equipment is rather novel in business cycle literature. This further distinction is pursued because ISTC exhibits very different patterns when separated according to the source of innovations. During the post-war sample the evolution of ISTC in ICT varies greatly from that

. (out2i,t) refers to imports of intermediate goods from manufacturing industries outside industry i to industry i relative to gross output. log(GO) refers to the log of gross output in total manufacturing. Technology change refers to lagged investment-specific technical change in industry i. All regressions include a first order autoregressive process (not reported). t-statistics are White Heteroscedasticity consistent. *** significant at 1 pct. level, ** significant at 5 pct. level, and * significant at 10 pct. level. Source: IDA, Statistics Denmark (2000

Journal of Ecomomics, 117: 339–76. BRESNAHAN, T. F. AND TRAJTENBERG, M. R. (1995). General Purpose Tech- nologies ’Engines of Growth’? Journal of Econometrics, 65: 83–108. BRYNJOLFSSON, E. AND HITT, L. (2000). Beyond Computation: Information Technology, Organizational Trasformation and Business Performance. Journal of Economic Perspectives, 14: 23–48. CUMMINS, J. G. AND VIOLANTE, G. (2002). Investment Specific Technical Change in the United States (1947-2000): Measurement and Macroeconomic Consequences. Review of Economic Dynamics, 5: 243–84. DASGUPTA, D. AND MARJIT, S

(2003). __________ “On the Aggregate Labor Supply,” Federal Reserve Bank of Richmond, Economic Quarterly 91 (Winter 2005). Christiano, Lawrence J. and Terry J. Fitzgerald, “The Band Pass Filter,” International Economic Review 44 (2003), 435-65. Collard, Fabrice “Spectral and Persistence Properties of Cyclical Growth,” Journal of Economic Dynamics and Control 23 (1999) 463-488. Cummins, Jason G., and Giovanni L. Violante, “Investment-Specific Technical Change in the United States (1947-2000): Measurement and Applications.” Review of Economic Dynamics 5 (2002), 243

support relatively high consumption levels when aid payments revert back to normal levels, and therefore consumption levels will follow a smooth transition. The more temporary the change is perceived, the larger will be the effect on the savings rate, the capital stock, and output. Note that for both types of aid the responses follow standard macro-intuition. For TA, responses are identical to models with investment specific technical change. In those models, an investment specific technology shock affects the relative price of physical capital, whereas in our model a

Dynamics, 5, 742–747. Canova, F. (1998): “Detrending and business cycle facts,” Journal of Monetary Economics, 41, 475–512. Canova, F., D. Lopez-Salido, and C. Michelacci (2007): “Schumpeterian technol- ogy shocks,” Mimeo, Centre de Recerca en Economia Internacional (CREI). Cummins, J. G. and G. L. Violante (2002): “Investment-specific technical change in the us (1947-2000): Measurement and macroeconomic consequences,” Review of Economic Dynamics, 5, 243–284. Davis, S. J., R. J. Faberman, and J. Haltiwanger (2006): “The flow approach to labor markets: New data sources

Macroeconomics, 3, 1103–1133. Bloch, H. and M. Olive (2001): “Pricing over the cycle,” Review of Industrial Or- ganization, 19, 99–108. Boldrin, M., L. J. Christiano, and J. D. Fisher (2001): “Habit persistence, asset returns, and the business cycle,” American Economic Review, 91, 149–166. Chevillon, G. (2007): “Direct multi-step estimation and forecasting,” Journal of Economic Surveys, 21, 746–785. Cummins, J. and G. L. Violante (2002): “Investment-specific technical change in the us (1947-2000): Measurement and macroeconomic consequences,” Review of Economic Dynamics, 5, 243

first change from to (A.3) to (A.5) (and welfare from (A.4) to (A.6)). Then, when the follower invests in R&D, the profit changes from (A.5) to (A.7) (and welfare from (A.6) to (A.8)). References Beath, J., Katsoulacos, Y., and Ulph, D. “Strategic R&D Policy.”Economic Journal, 99, (1989), pp. 74-83. Cummins, J.G., and Violante, G.L. “Investment-Specific Technical Change in the United States (1947-2000): Measurement and Macroeconomic Consequences.” Review of Economic Dynamics, 5, (2002), pp. 243-284. Cohen, W.M., Goto A., Nagata A., Nelson R.R., and Walsh, J.P., “R

till the end of the sample following the method de- scribed in J. Cummins and G. Violante (2002) “Investment-Specific Technical Change in the Unites States (1947-2000): Measurement and Macroeconomic Consequences”, Review of Economic Dynamics, Vol. 5, pp. 243-284. Price mark-up is an index defined as the ratio of the GDP deflator to the unit labor costs. Series of unit labor costs are taken from the OECD Unit Labour Costs Database and the International Labor Comparison elaborated by the U.S. Bureau of Labor Statistics. For Spain, the data start in 1979, we extrapolate