The Inequality of Influence

This paper develops a proxy measure of the inequality of influence on the basis of survey evidence from 2002 Business Environment and Enterprise Performance Survey (BEEPS) conducted among 6,500 firms in 27 transition countries. We refer to the resulting inequality as crony bias in the political system that can be measured at both the firm and country level. We examine the impact of crony bias at both the firm and country levels on three indicators of institutional subversion: 1) perceptions of and interaction with courts; 2) security of property rights; 3) tax compliance; and 4) bribery. We find a consistent pattern in which the inequality of influence has a strongly negative impact on assessments of public institutions that ultimately affects the behavior of firms towards those institutions. Crony bias at both the firm and the country levels is associated with a significantly more negative assessment of the fairness and impartiality of courts and the enforceability of court decisions. Further, firms that report crony bias are significantly less likely to use courts to resolve business disputes. Such firms are shown to have less secure property rights than more influential firms. We also find that crony bias is associated with lower levels of tax compliance and significantly higher levels of bribery. The evidence suggests that the inequality of influence not only damages the credibility of institutions among weak firms, but affects the likelihood that they will use and provide tax resources to support such institutions. By withholding tax revenues, paying bribes, and avoiding courts, these firms ensure that such state institutions are likely to remain weak and subject to capture by the more influential. The inequality of influence thus appears to generate a self-reinforcing dynamic in which institutions are subverted further strengthening the underlying political and economic inequalities.transition economies, crony bias, bribery, corruption, governance, tax compliance, courts, property rights, public institutions

Adaptive Bernstein-von Mises theorems in Gaussian white noise

We investigate Bernstein-von Mises theorems for adaptive nonparametric Bayesian procedures in the canonical Gaussian white noise model. We consider both a Hilbert space and multiscale setting with applications in $L^2$ and $L^\infty$ respectively. This provides a theoretical justification for plug-in procedures, for example the use of certain credible sets for sufficiently smooth linear functionals. We use this general approach to construct optimal frequentist confidence sets based on the posterior distribution. We also provide simulations to numerically illustrate our approach and obtain a visual representation of the geometries involved.Comment: 48 pages, 5 figure

Credibility of fiscal policy and politics: an empirical assessment

In this paper we address the measurement and the analysis of credibility in fiscal policy. In many instances fiscal policy as conducted by governments is not perceived as credible, because the targets set forward by the government are often not met. Usually the divergence is on the negative side. Taxes are overestimated and spending is underestimated, leading to a deficit bias and growing indebtedness of governments. This paper focuses on a measure of credibility that builds on the deviations of the actual budget balances from the projections about these balances in the preceding year for 26 EU member states over the period 1999-2009.1 The objective is to extract from these data insights into the credibility of these governments’ fiscal policies and to explain credibility by a number of political determinant

Maximum-a-posteriori estimation with Bayesian confidence regions

Solutions to inverse problems that are ill-conditioned or ill-posed may have significant intrinsic uncertainty. Unfortunately, analysing and quantifying this uncertainty is very challenging, particularly in high-dimensional problems. As a result, while most modern mathematical imaging methods produce impressive point estimation results, they are generally unable to quantify the uncertainty in the solutions delivered. This paper presents a new general methodology for approximating Bayesian high-posterior-density credibility regions in inverse problems that are convex and potentially very high-dimensional. The approximations are derived by using recent concentration of measure results related to information theory for log-concave random vectors. A remarkable property of the approximations is that they can be computed very efficiently, even in large-scale problems, by using standard convex optimisation techniques. In particular, they are available as a by-product in problems solved by maximum-a-posteriori estimation. The approximations also have favourable theoretical properties, namely they outer-bound the true high-posterior-density credibility regions, and they are stable with respect to model dimension. The proposed methodology is illustrated on two high-dimensional imaging inverse problems related to tomographic reconstruction and sparse deconvolution, where the approximations are used to perform Bayesian hypothesis tests and explore the uncertainty about the solutions, and where proximal Markov chain Monte Carlo algorithms are used as benchmark to compute exact credible regions and measure the approximation error

Remarks on the energy of regular graphs

The energy of a graph is the sum of the absolute values of the eigenvalues of its adjacency matrix. This note is about the energy of regular graphs. It is shown that graphs that are close to regular can be made regular with a negligible change of the energy. Also a $k$-regular graph can be extended to a $k$-regular graph of a slightly larger order with almost the same energy. As an application, it is shown that for every sufficiently large $n,$ there exists a regular graph $G$ of order $n$ whose energy $\left\Vert G\right\Vert_{\ast}$ satisfies $$\left\Vert G\right\Vert_{\ast}>\frac{1}{2}n^{3/2}-n^{13/10}.$$ Several infinite families of graphs with maximal or submaximal energy are given, and the energy of almost all regular graphs is determined.Comment: 12 pages. V2 corrects a typo. V3 corrects Theorem 1

Monetary policy in the Euro area: Lessons from 5 years of ECB and implications for Turkey

We examine monetary policy in the Euro area from both theoretical and empirical perspectives. We discuss what theory tells us the strategy of Central banks should be and contrasts it with the one employed by the ECB. We review accomplishments (and failures) of monetary policy in the Euro area and suggest changes that would increase the correlation between words and actions; streamline the understanding that markets have of the policy process; and anchor expectation formation more strongly. We examine the transmission of monetary policy shocks in the Euro area and in some potential member countries and try to infer the likely effects occurring when Turkey joins the EU first and the Euro area later. Much of the analysis here warns against having too high expectations of the economic gains that membership to the EU and Euro club will produce.Pillars, Communication, Transmission, EU newcomers