Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange

This paper investigates the use of tick-by-tick data for intraday market risk measurement. We propose a method to compute an Intraday Value at Risk based on irregularly spaced high-frequency data and an intraday Monte Carlo simulation. A log-ACD–ARMA–EGARCH model is used to specify the joint density of the marked point process of durations and high-frequency returns. We apply our methodology to transaction data for three stocks actively traded on the Toronto Stock Exchange. Compared to traditional techniques applied to intraday data, our methodology has two main advantages. First, our risk measure has a higher informational content as it takes into account all observations. On the total risk measure, our method allows for distinguishing the effect of random trade durations from the effect of random returns, and for analyzing the interaction between these factors. Thus, we find that the information contained in the time between transactions is relevant to risk analysis, which is consistent with predictions from asymmetric-information models in the market microstructure literature. Second, once the model has been estimated, the IVaR can be computed by any trader for any time horizon based on the same information and with no need of sampling the data and estimating the model again when the horizon changes. Backtesting results show that our approach constitutes reliable means of measuring intraday risk for traders who are very active in the market.     

Transaction costs and crop marketing in the communal areas of Impendle and Swayimana,KwaZulu-Natal

High transaction costs are detrimental to the efficient operation or existence of markets for inputs and outputs. The cost of information and the costs associated with the search for trade partners, the distance to formal markets and contract enforcement are likely to influence the marketing of food crops. This study hypothesises that the level of income generated from food-crop sales by small-scale farmers in the Impendle and Swayimana districts of KwaZuluNatal is influenced by transaction costs and certain household and farm characteristics. Regression analysis shows that the depth of marketing methods is significantly influenced by transaction cost proxies, such as cooperation with large commercial farmers and ownership of means of transport. Results from a block-recursive regression analysis show that the level of crop income generated is determined by the depth of marketing methods, the size of allocated arable land and off-farm income. Households with lower transaction costs, sizeable allocated land and off-farm income can be expected to generate higher income from food crops. Investment in public goods such as roads, telecommunications and an efficient legal system (to uphold commercial contracts), as well as farmer support services (input supply, extension, marketing information and research), would probably raise farm and non-farm income by reducing transaction costs. This would increase the effective demand for locally produced goods and services, thus contributing to rural employment and livelihoods within rural communal areas.     

Why not fully spend a conditional block grant?

This paper studies a conditional block grant that Dutch municipalities receive for welfare-to-work programs. Many municipalities do not fully use this grant, although programs are beneficial for them. We argue that municipalities incur expenses to use the grant. If these costs are substantial, then it is optimal not to fully use the grant. Based on municipality-specific data on grants and actual expenditures, we estimate that municipalities have to add about 90 cents from their own resources to spend 1 euro of the grant. As a result, the conditional block grant is de facto a closed-ended matching grant.     

The relevance of currency risk in the EMU

We investigate how the elimination of intra-European exchange risk may affect international financial markets using a conditional version of the International CAPM. We estimate the EMU and non-EMU components of aggregate currency risk and document significant exposures to both. The premium for EMU risk is positive and associated with exposure to the French, Italian and Spanish currencies. The premium for non-EMU risk is consistently negative and accounts for most of the aggregate currency premiums. In the 1990s, exposures to EMU risk declined significantly while exposures to non-EMU risk increased. Hence the adoption of the Euro is unlikely to have a large impact on aggregate currency risk premiums.     

A Classification of Dutch Manufacturing based on a Model of Innovation

Summary The paper studies the degree of homogeneity of innovative behavior in order to determine empirically an industry classification of Dutch manufacturing that can be used for policy purposes. Defining homogeneity in terms of an economic model distinguishes our classification from existing taxonomies such as those of the OECD, Pavitt and the various classifications based on a principal components analysis. We use a two-limit tobit model with sample selection, which explains the decisions by business enterprises to innovate and the impact these decisions have on the share of innovative sales. The model is estimated for eleven industries based on the Dutch Standard Industrial Classification (SBI 1993). A likelihood ratio (LR) test is then performed to test for equality of the parameters across industries. We find that Dutch manufacturing consists of three groups of industries in terms of innovative behavior, a high-tech group, a low-tech group and the industry of wood. The same pattern shows up in the three Dutch Community Innovation Surveys. The empirical part of this study has been carried out at the Centre for Research of Economic Microdata at Statistics Netherlands. The authors wish to thank Statistics Netherlands, and in particular Bert Diederen, for helping us in accessing and using the Micronoom data set. The views expressed in this paper are solely those of the authors. The authors also wish to thank Fran?ois Laisney, Patrick Waelbroek and participants at presentations in Maastricht, Strasbourg, Leuven and Lille for their helpful comments. The first author acknowledges financial support from METEOR.     

Urbanization effects on survey nonresponse: a test within and across cities

This paper addresses differences in survey response across city size by applying an explanation from House and Wolf to areas within cities. The data are from Toronto, Hamilton and Kitchener, in Canada. Consistent with other literature, response falls sharply from largest to smallest place, but variation in response rates within the cities is negligible. The intra-city analysis is accomplished by factor analyzing variables such as population density, crime rate and ethnic structure, mostly computed for census tracts, into a variable labelled social disorganization. What House and Wolf termed compositional variation in response is handled by record linking with municipal assessment information. The analysis is based on micro data taking the people listed for the sample as unit of observation.     

Health,Education and Emergence from the Development Trap

Abstract: This paper studies the emergence of developing countries from a development trap. It shows that countries whose dynamics exhibits several growth peaks can be considered as cases of equilibrium jump. Applying this criterion to a sample of 65 countries that were initially very poor in 1950, it identifies 13 such countries, called ‘emerging economies’. Comparing emerging and non‐emerging economies in the 1950s and early 1960s, it shows that economic take‐offs starting in the 1960s can be related to health and education in the early 1950s, while other possible factors, such as savings, openness and democracy are not significant.