TY - JOUR AU - Jones,Larry AU - Manuelli,Rodolfo AU - Siu,Henry TI - Growth and Business Cycles JF - National Bureau of Economic Research Working Paper Series VL - No. 7633 PY - 2000 Y2 - April 2000 UR - http://www.nber.org/papers/w7633 L1 - http://www.nber.org/papers/w7633.pdf N1 - Author contact info: Larry E. Jones Department of Economics University of Minnesota 4-101 Hanson Hall 1925 Fourth Street South Minneapolis, MN 55455 Tel: 612/624-4553 Fax: 612/624-0209 E-Mail: lej@umn.edu Rodolfo Manuelli Department of Economics Washington University in St. Louis Campus Box 1208; St. Louis, MO 63130-4899 Tel: 608/263-3877 Fax: 608/262-2033;608/263-3876 E-Mail: manuelli@artsci.wustl.edu Henry E. Siu Department of Economics University of British Columbia 1873 East Mall #997 Vancouver, BC V6T 1Z1 Canada Tel: 604/822-2919 Fax: 604/822-5915 E-Mail: hankman@mail.ubc.ca AB - Our purpose in this paper is to present a class of convex endogenous growth models, and to analyze their performance in terms of both growth and business cycle criteria. The models we study have close analogs in the real business cycle literature. In fact, we interpret the exogenous growth rate of productivity as an endogenous growth rate of human capital. This perspective allows us to compare the strengths of both classes of models. In order to highlight the mechanism that gives endogenous growth models the ability to improve upon their exogenous growth relatives, we study models that are symmetric in terms of human and physical capital formation -- our two engines of growth. More precisely, we analyze models in which the technology used to produce human capital is identical to the technologies used to produce consumption and investment goods, and in which the technology shocks in the two sectors are perfectly correlated. We find that endogenous growth models can generate levels of labor volatility close to those observed in the data, as well as positively correlated growth rates of output. We also find that these models outperform a related exogenous growth version in most dimensions. ER -