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The dynamics of entrepreneurial careers in high-tech ventures: experience, education, and exit
(2016)
We investigate the career dynamics of high-tech entrepreneurs by analyzing the exit choice of entrepreneurs: to found another firm, to become dependently employed, or to act as a business angel. Our detailed data resting on the CrunchBase online database indicate that founders stick with entrepreneurship as a serial entrepreneur or as an angel investor only in cases where the founder (1) had experience either in founding other startups or working for a startup, (2) had a ‘jack-of-all-trades’ education, or (3) achieved substantial financial success upon a venture capital exit transaction.
This study examines the role of actual and perceived financial sophistication (i.e., financial literacy and confidence) for individuals' wealth accumulation. Using survey data from the German SAVE initiative, we find strong gender- and education-related differences in the distribution of the two variables and their effects on wealth: As financial literacy rises in formal education, whereas confidence increases in education for men but decreases for women, we observe that women become strongly underconfident with higher education, while men remain overconfident.Regarding wealth accumulation, we show that financial literacy has a positive effect that is stronger for women than for men and that is increasing (decreasing) in education for women (men). Confidence, however, supports only highly-educated men's wealth. When considering different channels for wealth accumulation, we observe that financial literacy is more important for current financial market participation, whereas confidence is more strongly associated with future-oriented financial planning. Overall, we demonstrate that highly-educated men's wealth levels benefit from their overconfidence via all financial decisions considered, but highly-educated women's financial planning suffers from their underconfidence. This may impair their wealth levels in old age.
As the financial crisis gathered momentum in 2007, the United States Federal Reserve brought its policy interest rate aggressively down from 5¼ percent in September 2007 to virtually zero by December 2008. In contrast, although facing the same economic and financial stress, the European Central Bank’s first action was to raise its policy rate in July 2008. The ECB began lowering rates only in October 2008 once near global financial meltdown left it with no choice. Thereafter, the ECB lowered rates slowly, interrupted by more hikes in April and July 2011. We use the “abnormal” increase in stock prices — the rise in the stock price index that was not predicted by the trend in the previous 20 days — to measure the market’s reaction to the announcement of the interest rate cuts. Stock markets responded favorably to the Fed interest rate cuts but, on average, they reacted negatively when the ECB cut its policy rate. The Fed’s early and aggressive rate cuts established its intention to provide significant monetary stimulus. That helped renew market optimism, consistent with the earlier economic recovery. In contrast, the ECB started building its shelter only after the storm had started. Markets interpreted even the simulative ECB actions either as “too little, too late” or as signs of bad news. We conclude that by recognizing the extraordinary nature of the circumstances, the Fed’s response not only achieved better economic outcomes but also enhanced its credibility. The ECB could have acted similarly and stayed true to its mandate. The poorer economic outcomes will damage the ECB’s long-term credibility.
Chen and Zadrozny (1998) developed the linear extended Yule-Walker (XYW) method for determining the parameters of a vector autoregressive (VAR) model with available covariances of mixed-frequency observations on the variables of the model. If the parameters are determined uniquely for available population covariances, then, the VAR model is identified. The present paper extends the original XYW method to an extended XYW method for determining all ARMA parameters of a vector autoregressive moving-average (VARMA) model with available covariances of single- or mixed-frequency observations on the variables of the model. The paper proves that under conditions of stationarity, regularity, miniphaseness, controllability, observability, and diagonalizability on the parameters of the model, the parameters are determined uniquely with available population covariances of single- or mixed-frequency observations on the variables of the model, so that the VARMA model is identified with the single- or mixed-frequency covariances.
It has been forty years since the oil crisis of 1973/74. This crisis has been one of the defining economic events of the 1970s and has shaped how many economists think about oil price shocks. In recent years, a large literature on the economic determinants of oil price fluctuations has emerged. Drawing on this literature, we first provide an overview of the causes of all major oil price fluctuations between 1973 and 2014. We then discuss why oil price fluctuations remain difficult to predict, despite economists’ improved understanding of oil markets. Unexpected oil price fluctuations are commonly referred to as oil price shocks. We document that, in practice, consumers, policymakers, financial market participants and economists may have different oil price expectations, and that, what may be surprising to some, need not be equally surprising to others.