Consistency of Bayesian Linear Model Selection With a Growing Number of Parameters

Linear models with a growing number of parameters have been widely used in modern statistics. One important problem about this kind of model is the variable selection issue. Bayesian approaches, which provide a stochastic search of informative variables, have gained popularity. In this paper, we will study the asymptotic properties related to Bayesian model selection when the model dimension $p$ is growing with the sample size $n$. We consider $p\le n$ and provide sufficient conditions under which: (1) with large probability, the posterior probability of the true model (from which samples are drawn) uniformly dominates the posterior probability of any incorrect models; and (2) with large probability, the posterior probability of the true model converges to one. Both (1) and (2) guarantee that the true model will be selected under a Bayesian framework. We also demonstrate several situations when (1) holds but (2) fails, which illustrates the difference between these two properties. Simulated examples are provided to illustrate the main results

Corruption and Cross-Border Investment: Firm-Level Evidence

This paper studies the impact of corruption on inward foreign direct investment using a unique firm-level data set. It examines two effects of corruption simultaneously: a reduction in the volume of foreign investment and a shift in the ownership structure. Corruption makes local bureaucracy less transparent and hence acts as a tax on foreign investors. Moreover, corruption affects the decision to take on a local partner. On the one hand, corruption increases the value of using a local partner to cut through the bureaucratic maze. On the other hand, corruption decreases the effective protection of investor’s intangible assets and lowers the probability that disputes between foreign and domestic partners will be adjudicated fairly, which reduces the value of having a local partner. The importance of protecting intangible assets increases with investor’s technological sophistication, which tilts the preference away from joint ventures in a corrupt country. Empirical evidence shows that corruption reduces inward FDI and shifts the ownership structure towards joint ventures. Technologically more advanced firms are found to be less likely to engage in joint ventures.http://deepblue.lib.umich.edu/bitstream/2027.42/39879/3/wp494.pd

Corruption and the composition of foreign direct investment - firm-level evidence

The authors study the impact of corruption in a host country on foreign investors'preference for a joint venture, or a wholly owned subsidiary. Their simple model highlights a basic tradeoff in using local partners. On the one hand, corruption makes the local bureaucracy less transparent, and increases the value of using a local partner to cut through the bureaucratic maze. On the other hand, corruption decreases the effective protection of an investors'intangible assets, and reduces the probability that disputes between foreign and domestic partners, will be adjudicated fairly, which reduces the value of having a local partner. As the investor's technological sophistication increases, so does the importance of protecting intangible assets, which tilts the preference away from joint ventures in a corrupt country. Empirical tests of this hypothesis on firm-level data show that corruption reduces inward foreign direct investment, and shifts the ownership structure toward joint ventures. Conditional on foreign direct investment taking place, an increase in corruption from the level found in Hungary to that found in Azerbaijan, decreases the probability of a wholly owned subsidiary by 10 to 20 percent. Technologically more advanced firms are less likely to engage in joint ventures, however. The authors find support for the view that U.S. firms are more averse to joint ventures in corrupt countries than other foreign investors - possibly because the U.S. Foreign corrupt Practices Act, which stipulates penalties for executives of U.S. companies whose employees, or local partners engage in paying bribes. But although U.S. companies are more likely than investors from other countries to retain full ownership of firms in corrupt countries, they are not less likely than firms from other countries to undertake foreign direct investment in thosecountries.International Terrorism&Counterterrorism,Fiscal&Monetary Policy,Decentralization,Economic Theory&Research,Legal Products,International Terrorism&Counterterrorism,Governance Indicators,National Governance,Foreign Direct Investment,Legal Products

Corruption and Cross-Border Investment: Firm-Level Evidence

This paper studies the impact of corruption on inward foreign direct investment using a unique firm-level data set. It examines two effects of corruption simultaneously: a reduction in the volume of foreign investment and a shift in the ownership structure. Corruption makes local bureaucracy less transparent and hence acts as a tax on foreign investors. Moreover, corruption affects the decision to take on a local partner. On the one hand, corruption increases the value of using a local partner to cut through the bureaucratic maze. On the other hand, corruption decreases the effective protection of investor’s intangible assets and lowers the probability that disputes between foreign and domestic partners will be adjudicated fairly, which reduces the value of having a local partner. The importance of protecting intangible assets increases with investor’s technological sophistication, which tilts the preference away from joint ventures in a corrupt country. Empirical evidence shows that corruption reduces inward FDI and shifts the ownership structure towards joint ventures. Technologically more advanced firms are found to be less likely to engage in joint ventures.Corruption, Foreign direct investment, Multinational firms

Restoration of missing lines in grip patterns for biometrics authentication on a smart gun

The Secure Grip project1 aims to develop a grip-pattern recognition system, as part of a smart gun. Its target users are the police officers. The current authentication algorithm is based on a likelihood-ratio classifier. The grip pattern is acquired by sensors on the grip of the gun. Since in practice various factors can result in missing lines in a grip pattern, restoration of these missing lines will be useful and practical. We present a restoration algorithm based on null-space error minimization. The simulation results of the restoration and authentication experiments show that this restoration algorithm effectively restores grip patterns, and is, therefore, capable of improving the system’s authentication performance when missing lines are present