-
Abstract
The international diffusion of technology plays a key role in stimulating global growth and explaining co-movements of international equity returns. Existing empirical evidence suggests that countries are heterogeneous in their attitude toward innovation: Some countries rely more on technology adoption while other countries rely more on internal technology production. European countries that rely more on adoption are also typically characterized by lower fiscal policy flexibility and higher labor market rigidity. We develop a two-country model, in which both countries rely on R&D and adoption, to study the shortand long-run effects of aggregate technology and adoption probability shocks on economic growth in the presence of the aforementioned asymmetries. Our framework suggests that an increase in the ability to adopt technology from abroad stimulates future economic growth in the country that benefits from higher adoption rates but the beneficial effects also spread to the foreign country. Moreover, it helps to explain the differences in macro quantities and equity returns observed in the international data.
JEL Codes: E3, F3, F4, G12.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Technology trade with asymmetric tax regimes and heterogeneous labor markets: Implications for macro quantities and asset prices
Investment-specific shocks, business cycles, and asset prices
-
Abstract
This paper proposes and tests a new source of time variation in real investment opportunities, namely long-run shocks to the productivity of the investment sector, to explain the joint behavior of macroeconomic quantities and asset prices. A two-sector general equilibrium model with long-run investment shocks and wage rigidities produces both positive co-movement among key macroeconomic variables and a sizable return volatility differential between the investment and consumption sector. Moreover, positive long-run investment shocks are associated with low marginal utility and thus command a positive risk premium. We test our model using data on sectoral TFP and find evidence in support of our theoretical predictions.
JEL Codes: E32, G12.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.