The demand for money in Bulgaria is estimated over a ten-year period (1991–2000) of high inflation and inflation uncertainty. The paper distinguishes between three well-defined sub-periods: high, variable, but not systematically accelerating inflation from 1991 until April 1996; the near-hyperinflation period from May 1996 to February 1997; and the subsequent stabilization after the adoption of a currency board. The empirical analysis utilizes a standard methodology of cointegration and error correction. The functional determinants of the demand for money change during the different sub-periods. During the hyperinflation episode, Cagan's model is employed.

Innovation ecosystems use R&D inputs to generate innovation outputs first and innovation impacts later. But some countries show a relatively low transmission, such as in the case of Kazakhstan, the largest economy in Central Asia. This article analyzes the transmission from R&D into innovation outputs and impacts through a framework for which different factors matter, such as the company size, education and skills, competition, exports, and foreign ownership. Transmission is conceptually understood in two steps: from R&D into innovation outputs, and from innovation output into innovation impacts. The main hypothesis is that the high endowments of these company factors should lead to the better transmission of results and improved performance in terms of outputs and impacts. We test this using new evidence from Kazakhstan and the ECA region (Europe and Central as defined by the World Bank) as benchmarking, and data are from the Global Innovation Index (descriptive section) and the World Bank Enterprise Surveys (analytical section). The econometrics are a Crépon–Duguet–Mairesse (CDM) model in three steps: factors for propensity to invest in R&D, then to innovate, and, finally, innovation impacts on productivity. Results confirm the positive roles of factors, such as exports and education, in positive transmissions and uneven or insignificant results on productivity impacts from characteristics, such as age, size, and foreign ownership. The specifics for Kazakhstan suggest a potential for business innovation growth in the country. The paper concludes by suggesting key policy measures to unlock the potential for business innovation at a country level.