We analyze recent contributions to growth theory based on the model of expanding variety of Romer (1990). In the first part, we present different versions of the benchmark linear model with imperfect competition. These include the “labequipment” model, labor-for-intermediates” and...

We use the historical self-employment rate as an indicator of a regional culture of entrepreneurship and link this measure to economic growth in recent periods. The results indicate that German regions with a high level of entrepreneurship in the mid- 1920s have higher start-up rates about 80...

We investigate the persistence of levels of self-employment and new business formation in different time periods and under different framework conditions. The analysis shows that high levels of regional self-employment and new business formation tend to be persistent for periods as long as 80...

We distinguish four types of regional growth regimes based on the type of relationship between new business formation and economic development. The distinguishing characteristics of these regime types are analyzed in order to identify the reasons for different growth performance. Although growth...

Let a class $\F$ of densities be given. We draw an i.i.d.\ sample from a density $f$ which may or may not be in $\F$. After every $n$, one must make a guess whether $f \in \F$ or not. A class is almost surely testable if there exists such a testing sequence such that for any $f$, we make...

For the standard kernel density estimate, it is known that one can tune the bandwidth such that the expected L1 error is within a constant factor of the optimal L1 error (obtained when one is allowed to choose the bandwidth with knowledge of the density). In this paper, we pose the same problem...

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provide explicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate, and study in...

We use aggregate GDP data and within-country income shares for the period 1970-1998 to assign a level of income to each person in the world. We then estimate the gaussian kernel density function for the worldwide distribution of income. We compute world poverty rates by integrating the density...