Corruption in space: A closer look at the world's subnations

Corruption levels differ not only between but also within countries. In this paper we analyze spatial interdependencies in corruption levels for a large sample of 1232 subnational regions from 81 countries. Based on a spatial autoregressive model, which controls for country-fixed effects and corrects for spatial autocorrelation in the error term, we find that a subnational region's corruption level is positively correlated with neighboring subnational regions' corruption levels. Extending the core model and allowing for heterogeneous spatial effects, we find that most spillovers among subnational regions occur within national borders. Moreover, in particular high income subnational regions and subnational regions with relative low corruption levels tend to spill in space. This is due to their high degree of connectivity in terms of economic, sociocultural and political exchange with other subnational regions. Our estimation results underline the importance to consider not only a subnational region's own characteristics, but also spatial interdependencies when implementing efficient anti-corruption policies at the local level.     

Consumption,welfare, and stochastic population dynamics when technology shocks are (Un)tied

The impact of uncertainty on consumption and welfare seems obvious; because of the precautionary saving motive, higher uncertainty reduces consumption, and subsequently, deteriorates welfare. Recent several studies, however, find that this intuitive narrative is not necessarily true. This paper provides the analytical underpinnings for this. In the absence of technological progress, I find that the larger demographic shocks always reduce consumption, but improve the welfare of households. Moreover, when demographic shocks are negatively tied to technology shocks, there emerges an inverted-U relationship between the size of two shocks and consumption, and a U-shaped relationship between the size of two shocks and household welfare. These results are all characterized analytically in the framework of the stochastic two-sector growth model featuring the correlated Brownian motion process. The findings suggest that demographic policies should not be implemented with no reference to the state of technology.     

TOOLS FOR RE‐RANDOMIZATION

With the rising popularity of field experiments in economics, re‐randomization schemes have emerged as tools to induce balance in observable variables across treatment groups. However, re‐randomization is not fully understood and the methodologies to estimate its effects on the distribution of parameters are still under‐developed. This paper helps to close that gap by suggesting an asymptotically normal re‐randomization scheme and bootstrapping procedure to carry inference under a wide range of estimators and re‐randomization schemes.     

Negotiating with Terrorists: The Costs of Compliance

It is often argued that negotiating with terrorists will encourage terrorist attacks. To date, corroborating empirical evidence is scarce. Using ITERATE data, we investigate the impact of conceding to terrorist demands on terror activity. We restrict attention to hostage events with clear‐cut demands from terrorists. Our sample period runs from 1978 to 2005 and comprises 1435 events in 125 countries. Estimating a flexible and dynamic Structured Additive Regression model, we find that the percentage of successfully negotiated events has a nonlinear effect on future terror intensity consistent with our simple theoretical model. More specifically, although moderate rates of negotiation increase the number of future terror events, higher negotiation rates tend to have the opposite effect. The estimated threshold is around 20%.     

Concentration behavior of the penalized least squares estimator

Consider the standard nonparametric regression model and take as estimator the penalized least squares function. In this article, we study the trade‐off between closeness to the true function and complexity penalization of the estimator, where complexity is described by a seminorm on a class of functions. First, we present an exponential concentration inequality revealing the concentration behavior of the trade‐off of the penalized least squares estimator around a nonrandom quantity, where such quantity depends on the problem under consideration. Then, under some conditions and for the proper choice of the tuning parameter, we obtain bounds for this nonrandom quantity. We illustrate our results with some examples that include the smoothing splines estimator.     

Bagging bundle benefits in broadband and media mergers: Lessons from Sky/Vodafone for antitrust analysis

The historic precedents in telecommunications antitrust findings have tended towards finding harm to competition when network operators integrate downstream and bundle the provision of applications and services. The reason for this is that market power in network provision is thought to be extended into the applications market(s). More recently however, proposed mergers have been between telecommunications and media distribution firms, both of whom have some degree of market power, already sell their own services in bundles, and who may or may not have been offering combined bundles already via contractual agreements. Examples include Sky/Vodafone in New Zealand, and Time Warner/AT&T in the United States as well as Vodafone/Unitymedia in Germany and Media Capital/Altice in Portugal. These complex proposed arrangements pose challenges to competition authorities, whose legal and procedural rules and precedents, especially those defining the relevant markets affected by the merger or vertical integration activity, have been developed from the analysis of simpler cases. These precedents may not be sufficient to analyse current cases, characterized by multiple products catering to heterogeneous consumer preferences, and consumers are not constrained to buying only one variant of the products in each of the upstream and downstream markets.We illustrate the challenges by way of a case study of the proposed merger between Sky and Vodafone, declined by the New Zealand Commerce Commission in February 2017. Limitations in existing market definition processes and the evaluation of market power where bundling already occurs risk overlooking complex demand-side interactions that influence the profitability and efficiency of various structural and contractual strategic choices. We propose that classic merger and antitrust analysis based on econometric cost-benefit analysis can be augmented by using simulation and numerical analysis of a range of bundle offers expected to be relevant in decision-making. We develop a simple model and use it to illustrate how it may be used to inform broadband and content mergers, and other complex antitrust cases, such the assessment of the effects of two-sided markets and firm pricing decisions.     

Does corruption slow down innovation? Evidence from a cointegrated panel of U.S. states

I investigate the long-run relationship between corruption and innovative activity using annual data from 48 contiguous U.S. states between 1977 and 2006. Using U.S. data allows me to work with a panel long enough to exploit time series properties of the data. I use two different measures of innovative activity: one measuring the quantity and the other measuring the quality of the patents granted. I also use two different measures of corruption: one based on the number of corruption convictions, the other based on number of corruption stories covered in Associated Press news wires. Following Pedroni (1999, 2000), I estimate the cointegrating relationship between corruption and innovative activity with Fully Modified Ordinary Least Squares (FMOLS). The results indicate that corruption indeed slows down innovation in the long-run.     

The short‐time behavior of VIX‐implied volatilities in a multifactor stochastic volatility framework

We consider a modeling setup where the volatility index (VIX) dynamics are explicitly computable as a smooth transformation of a purely diffusive, multidimensional Markov process. The framework is general enough to embed many popular stochastic volatility models. We develop closed‐form expansions and sharp error bounds for VIX futures, options, and implied volatilities. In particular, we derive exact asymptotic results for VIX‐implied volatilities, and their sensitivities, in the joint limit of short time‐to‐maturity and small log‐moneyness. The expansions obtained are explicit based on elementary functions and they neatly uncover how the VIX skew depends on the specific choice of the volatility and the vol‐of‐vol processes. Our results are based on perturbation techniques applied to the infinitesimal generator of the underlying process. This methodology has previously been adopted to derive approximations of equity (SPX) options. However, the generalizations needed to cover the case of VIX options are by no means straightforward as the dynamics of the underlying VIX futures are not explicitly known. To illustrate the accuracy of our technique, we provide numerical implementations for a selection of model specifications.     

Why cryptocurrency markets are inefficient: The impact of liquidity and volatility

In this research, we study the multifractality, long-memory process, and efficiency hypothesis of six major cryptocurrencies (Bitcoin, Ethereum, Monero, Dash, Litecoin, and Ripple) using the time-rolling MF-DFA approach. For an in-depth analysis, this study uses the quantile regression approach to examine the determinants of efficient markets. The results show that all markets present evidence of long-memory property and multifractality. Furthermore, the inefficiency of cryptocurrency markets is time-varying, and Dash is the least inefficient market while Litecoin is the most inefficient. Finally, we find that higher liquidity improves but higher volatility weakens the efficiency of cryptocurrencies, depending on the quantiles. Therefore, we conclude that high liquidity with low volatility helps active traders to arbitrage away opportunities, resulting in market efficiency.