Tests of Normality of Functional Data

The paper is concerned with testing normality in samples of curves and error curves estimated from functional regression models. We propose a general paradigm based on the application of multivariate normality tests to vectors of functional principal components scores. We examine finite sample performance of a number of such tests and select the best performing tests. We apply them to several extensively used functional data sets and determine which can be treated as normal, possibly after a suitable transformation. We also offer practical guidance on software implementations of all tests we study and develop large sample justification for tests based on sample skewness and kurtosis of functional principal component scores.     

Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading

We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used returns measured over 5 or 10 min intervals. We show that the new estimator is substantially more precise.     

Asymptotic properties of Monte Carlo estimators of diffusion processes

This paper studies the limit distributions of Monte Carlo estimators of diffusion processes. We examine two types of estimators based on the Euler scheme, one applied to the original processes, the other to a Doss transformation of the processes. We show that the transformation increases the speed of convergence of the Euler scheme. We also study estimators of conditional expectations of diffusions. After characterizing expected approximation errors, we construct second-order bias-corrected estimators. We also derive new convergence results for the Mihlstein scheme. Illustrations of the results are provided in the context of simulation-based estimation of diffusion processes.     

Utility of wealth with many indivisibilities

We introduce a class of utility of wealth functions, called knapsack utility functions, which are appropriate for agents who must choose an optimal collection of indivisible goods subject to a spending constraint. We investigate the concavity/convexity and regularity properties of these functions. We find that convexity–and thus a demand for gambling–is the norm, but that the incentive to gamble is more pronounced at low wealth levels. We consider an intertemporal version of the problem in which the agent faces a credit constraint. We find that the agent’s utility of wealth function closely resembles a knapsack utility function when the agent’s saving rate is low.     

The behaviour of betting and currency markets on the night of the EU referendum

We study the behaviours of the Betfair betting market and the sterling/dollar exchange rate (futures price) during 24 June 2016, the night of the EU referendum. We investigate how the two markets responded to the announcement of the voting results by employing a Bayesian updating methodology to update prior opinion about the likelihood of the final outcome of the vote. We then relate the voting model to the real-time evolution of the market-determined prices as the results were announced. We find that, although both markets appear to be inefficient in absorbing the new information contained in the vote outcomes, the betting market seems less inefficient than the FX market. The different rates of convergence to the fundamental value between the two markets lead to highly profitable arbitrage opportunities.     

Allocating chances of success in finite and infinite societies: The utilitarian criterion

We study a particular collective choice problem, that of allocating chances of success. We argue that many problems of interest have this nature, from small scale problems like medical triage to large scale ones like the allocation of opportunities in society. We consider both finite and infinite societies. We characterise utilitarian-type criteria by means of new properties tailored to the probabilistic structure of the alternatives.     

Some strange properties of panel data estimators

We study the biases that are likely to arise in practice with panel data when parameters vary across individuals, but this is not allowed for in estimation. We consider both stationary and non-stationary regressors. We find that biases can be severe for relatively small parameter variation, and that this problem is hard to detect. We study in some detail by Monte-Carlo the performance of the Anderson-Hsiao estimator in the presence of this particular mis-specification.     

The Three Basic Types of Residuals for a Linear Model

We consider residuals for the linear model with a general covariance structure. In contrast to the situation where observations are independent there are several alternative definitions. We draw attention to three quite distinct types of residuals: the marginal residuals, the model‐specified residuals and the full‐conditional residuals. We adopt a very broad perspective including linear mixed models, time series and smoothers as well as models for spatial and multivariate data. We concentrate on defining these different residual types and discussing their interrelationships. The full‐conditional residuals are seen to play several important roles.     

On the properties of a multiple sequential test

We consider a multiple testing problem based on an i.i.d. sample of K-dimensional observations. We want to test whether at least one of the unknown means is positive. We propose a sequential test which is of the nature of a multiple truncated sequential probability ratio test. We asymptotically analyse the expected sample size and compare it to the sample sizes which arise when one looks at effects separately.     

Factor pricing of cryptocurrencies

In this paper, we study the cryptocurrency pricing factors. We review the literatures which state that the cryptocurrency market is weakly efficient. We use the Fama–MacBeth method to investigate the pricing factors. The classical equity-based risk factors including size, momentum, and value to growth from the Fama–French three factor model are studied. We use crypto-unique coin-to-token as a proxy for value-to-growth. For volatility risk factor category, we investigate realized volatility, skewness and jump. We also investigate liquidity factors including bid–ask, volume growth and Roll’s measure. The macro factors are found not to be an explanatory factor. The attention factor works sometimes. The factor model constructed by the significant factors explain most of the excess return of cryptocurrencies.     

Foundations of logistics and supply chain research: a bibliometric analysis of four international journals

The purpose of this paper is to explore the current intellectual foundation of four leading academic journals within the field of logistics and supply chain management. We were interested to identify the most frequently quoted publications as well as their impact on logistics research. We examined 17,000 references of 412 papers and further analysed the 39 top-references with the means of multidimensional scaling (MDS), cluster- and factor analysis. We were able to identify a mix of textbooks and articles from academic journals and revealed a journal-specific citation pattern, not only in the choice of textbooks but also in the choice of referenced methodology papers. We were also able to identify citation streams and citation areas, where it was surprising to find so many general socio-scientific papers and general papers explaining the character of the field.     

The Role of Built,Human, Social,and Natural Capital in Determining Land Values,and the Influence of Demographics upon this Relationship

Abstract

We use various statistical methods to compare the extent to which different households are willing to invest in and pay for access to four types of capital—built, human, natural, and social. We further assess to what extent such preferences can be predicted by a measure of neighbourhood demographics. We develop indicators for each of the four types of capital at the census block group level for Baltimore, MD, USA. We use analysis of variance to examine differences in these indicators between demographic groups and multiple linear regression to examine the influence on unimproved land values of the four types of capital.     

The Macroeconomic Effects of Shocks to Large Banks’ Capital

We propose a simple approach to quantifying the macroeconomic effects of shocks to large banks’ leverage. We first estimate a standard dynamic model of leverage targeting at the bank level and use it to derive an aggregate measure of the economic capital buffer of large US bank holding corporations. We then evaluate the response of key macro variables to a shock to this aggregate bank capital buffer using standard monetary VAR models. We find that shocks to the capital of large US banks explain a substantial share of the variance of credit to firms and real activity.     

The value of information: The case of signal-dependent opportunity sets

We generalize the economic decision problem considered by Blackwell (1953) in which a decision-maker chooses an action after observing a signal correlated to the state of nature. Unlike Blackwell's case where the feasible set is fixed, in our framework the feasible set of actions depends on the signal and the information system. We argue that such a framework has more significance to economic models. As was demonstrated by Hirshleifer (1971) in such cases, contrary to Blackwell's well-known result, more information may be disadvantageous. We derive conditions for this general model which guarantee that more information is beneficial.     

The effects of oil price shocks on job reallocation

We investigate the effect of oil price innovations on U.S. manufacturing job flows using a simultaneous equation model that nests symmetric and asymmetric responses. We find no evidence of asymmetry in the response of job flows to positive and negative oil price innovations. We then inquire whether firms, when facing positive shocks, shed jobs faster than they create jobs. We show that positive innovations lead to a decline in net employment and an increase in job reallocation, possibly due to search and matching issues. Yet, the latter effect becomes statistically insignificant when we control for data mining. We demonstrate that the cumulative one-year effect of oil price shocks on job creation and destruction was smaller during the Great Moderation, but it was larger for gross job reallocation. These variations were caused by a change in the transmission channel and not by smaller oil price shocks.     

Reconfiguring a set of coverage-providing facilities under travel time uncertainty

We study networks of facilities that must provide coverage under conditions of uncertainty with respect to travel times and customer demand. We model this uncertainty through a set of scenarios. Since opening new facilities and/or closing existing ones is often quite expensive, we focus on optimal re-configuration of the network, that is finding a facility set that achieves desired thresholds with respect to expected and minimal coverage, while retaining as many of the existing facilities as possible. We illustrate our model with an example of Toronto Fire Service. We demonstrate that relocating just a few facilities can have the same effect as opening a similar number of new ones. We develop exact and approximate solution approaches and test them with computational experiments. Algorithm based on Tabu Search (with certain novel components) appears to be particularly successful for this problem. We also analyze the multi-objective version of the problem, where the expected and minimum coverage levels are treated as objectives in addition to the objective of maximizing the number of pre-existing facilities in the final location set.     

The effect of government highway spending on road users' congestion costs

Policymakers attempt to reduce the growth of congestion by spending billions of dollars annually on our road system. We evaluate this policy by estimating the determinants of congestion costs for motorists, trucking operations, and shipping firms. We find that, on average, one dollar of highway spending in a given year reduces the congestion costs to road users only eleven cents in that year. We also find that even if the allocation of spending were optimized to minimize congestion costs that it still is not a cost-effective way to reduce congestion. We conclude the evidence strengthens the case for road pricing.     

A general equilibrium analysis of strategic arbitrage

We analyze a general equilibrium framework with Cournot arbitrageurs and with price-taking investors who are subjected to restricted participation constraints. Restricted participation may leave some arbitrage opportunities unexploited by investors.We show existence of Cournot–Walras equilibria with an endogenous number of arbitrageurs. The number of arbitrageurs is endogenous since they have to sink entry costs in order to arbitrage across the relevant markets. We characterize equilibria and analyze the effects on equilibrium prices and quantities of increased competition among arbitrageurs due to lower entry costs.     

The Multiple Effects of Business Planning on New Venture Performance

We investigate the multiple effects of writing a business plan prior to start‐up on new venture performance. We argue that the impact of business plans depends on the purpose for and circumstances in which they are being used. We offer an empirical methodology which can account for these multiple effects while disentangling real impact effects from selection effects. We apply this to English data where we find that business plans promote employment growth. This is found to be due to the impact of the plan and not selection effects.