Cointegration and control: Assessing the impact of events using time series data

Control groups can provide counterfactual evidence for assessing the impact of an event or policy change on a target variable. We argue that fitting a multivariate time series model offers potential gains over a direct comparison between the target and a weighted average of controls. More importantly, it highlights the assumptions underlying methods such as difference in differences and synthetic control, suggesting ways to test these assumptions. Gains from simple and transparent time series models are analysed using examples from the literature, including the California smoking law of 1989 and German reunification. We argue that selecting controls using a time series strategy is preferable to existing data‐driven regression methods.     

Quasi‐fixed inputs and long‐run equilibrium in production: a cointegration analysis

This paper proposes a cointegration approach to testing the validity long‐run equilibrium in production, where capital and labour are taken as quasi‐fixed inputs. Previous studies consider only capital as the quasi‐fixed input and do not take account of the time series properties of the variables, assuming implicitly that they are stationary. The canonical cointegrating regressions (CCR) procedure is employed to test for cointegration in both the single‐equation and the seemingly unrelated regressions framework, and long‐run equilibrium conditions are tested. The evidence from US manufacturing reveals that capital and labour are not fully adjusted to their long‐run optimal values, casting doubt on the long‐run equilibrium hypothesis. Copyright © 2001 John Wiley & Sons, Ltd.     

The long‐run effect of government ideology on economic freedom

According to popular attitudes in Western democracies, the choice between right‐wing and left‐wing parties is a choice between socialism and unbridled free markets. In contrast, the cold and staid research of academia has frequently concluded that particular political parties do not really matter, as whichever party is elected will be closely tethered to the will of the median voter. This article considers the effects of the ideology of parties in power over the long run (1928–95) on economic freedom in subsequent periods. Right‐wing governments are found to have modest, positive effects on economic freedom, but the effects are not particularly robust. The findings here are consistent with others elsewhere, which conclude that there is minor, uneven evidence of an effect. Nonetheless, historically small effects may not be indicative of the future, should these effects be poorly indicative of today's tumultuous political landscape.     

Re‐evaluating the concept of working time: an analysis of recent case law

Controversy abounds the Working Time Directive seven years since its implementation as the European Commission seeks to unpick the compromise that led to the notorious individual opt‐out from maximum weekly working time. This article explores the roots of that controversy in the context of the Court of Justice’s expansive interpretation of the concept of ‘working time’. To what extent is it possible to maintain a health and safety guarantee but allow for more flexibility in the organisation of working time for individual workers in an increasingly heterogeneous working environment?     

Involuntary part‐time workers in Britain: evidence from the labour force survey

Part‐time employment is widely considered functional for the economy, with both benign and detrimental implications for employees. However, specific analyses of involuntary part‐time work in Britain are surprisingly absent from the flexibility debate, and workers in such positions remain largely under‐researched. This article explores involuntary part‐time employment in relation to socio‐economic circumstances. We analyse Labour Force Survey data, using logistic regression modelling to identify the segments of workers filling part‐time jobs involuntarily. The results suggest that involuntariness for part‐time jobs is affected by a range of demographic and work‐related characteristics considered. Being a couple with dependent children, for example, reduces the likelihood of involuntariness among female part‐time employees whereas lower educational and occupational levels imply a higher involuntariness across both sexes.     

Efficient tests of long‐run causation in trivariate VAR processes with a rolling window study of the money–income relationship

This paper develops a simple sequential multiple‐horizon non‐causation test strategy for trivariate VAR models (with one auxiliary variable). We apply the test strategy to a rolling window study of money supply and real income, with the price of oil, the unemployment rate and the spread between the Treasury bill and commercial paper rates as auxiliary processes. Ours is the first study to control simultaneously for common stochastic trends, sensitivity of test statistics to the chosen sample period, null hypothesis over‐rejection, sequential test size bounds, and the possibility of causal delays. Evidence suggests highly significant direct or indirect causality from M1 to real income, in particular through the unemployment rate and M2 once we control for cointegration. Copyright © 2007 John Wiley & Sons, Ltd.     

Charity registration and reporting: a cross-jurisdictional and theoretical analysis of regulatory impact

Governments increasingly regulate charities to restrict the number of organizations claiming taxation exemptions, reduce charities’ ability to abuse state support, and detect and deter fraud. Public interest theory arguments suggest that regulation could increase philanthropy through enhancing public trust and confidence in charities. Nevertheless, public choice theory argues that regulators seek to maximize political returns, ‘manage’ charity-government relationships, and reduce potential regulatory capture.

We analyse charity regulatory regimes using these two regulatory theories and the relative costs and benefits of different regulatory regimes. Heeding these should reduce regulatory inefficiency and balance accountability and transparency demands against benefits charities receive from regulation.     

Assessing the impact of crime on the economic performance: the case of central america

Crime is obviously a menace to economic growth and progress, but to acutely understand the enormity of its impact on economic performance for effective policy action, requires a credible means of measurement. Given the crime notoriety of the most of Central America and the struggling state of their economies, this article attempts to discern from econometric evaluation and analyses, the calculable economic impact of crime on the region’s economic progress. From analyses of results, we find the model to be credible and useful following its provision of a much more accurate degree to which crime affects economic performance in Central America, which we find critical to guide policy measures.     

Time series modeling of histogram-valued data: The daily histogram time series of S&P500 intradaily returns

Histogram time series (HTS) and interval time series (ITS) are examples of symbolic data sets. Though there have been methodological developments in a cross-sectional environment, they have been scarce in a time series setting. Arroyo, González-Rivera, and Maté (2011) analyze various forecasting methods for HTS and ITS, adapting smoothing filters and nonparametric algorithms such as the k-NN. Though these methods are very flexible, they may not be the true underlying data generating process (DGP). We present the first step in the search for a DGP by focusing on the autocorrelation functions (ACFs) of HTS and ITS. We analyze the ACF of the daily histogram of 5-minute intradaily returns to the S&P500 index in 2007 and 2008. There are clusters of high/low activity that generate a strong, positive, and persistent autocorrelation, pointing towards some autoregressive process for HTS. Though smoothing and k-NN may not be the true DGPs, we find that they are very good approximations because they are able to capture almost all of the original autocorrelation. However, there seems to be some structure left in the data that will require new modelling techniques. As a byproduct, we also analyze the [90,100%] quantile interval. By using all of the information contained in the histogram, we find that there are advantages in the estimation and prediction of a specific interval.     

Working time flexibility across Europe: a typology using firm‐level data

Using the European Establishment Survey of Working Times, we derive a typology of firms based on the mix of flexible working time practices they employ. Six flexibility profiles are distinguished, each representing a considerable proportion of establishments. The typology not only differentiates between more and less flexible firms, but also between the focus of the practices firms adopt, stressing that flexibility is not a one‐dimensional concept. We also investigate what firm characteristics are good predictors of the adoption of a certain flexibility profile and how the profiles are related to performance and perceived HRM bottlenecks.     

The use of time series processes to model the error structure of earnings in a longitudinal data analysis

This study presents an error structure that offers a rich statistical framework for panel data analysis. It includes as special cases most of the error specifications found in longitudinal studies of wages and earnings. A general set of procedures for choosing a specification of this error structure and estimating its parameters appears in the first part of this study. The last section applies these procedures to fit an error structure for wages and earnings of prime-age males using data from the Michigan Panel of Income Dynamics.     

Some asymptotic results of a non‐parametric conditional mode estimator for functional time‐series data

We consider the estimation of the conditional mode function when the covariates take values in some abstract function space. The main goal of this paper was to establish the almost complete convergence and the asymptotic normality of the kernel estimator of the conditional mode when the process is assumed to be strongly mixing and under the concentration property over the functional regressors. Some applications are given. This approach can be applied in time‐series analysis to the prediction and confidence band building. We illustrate our methodology by using El Nio data.     

The over‐training of apprentices by employers in advanced manufacturing: a theoretical and policy analysis

This article reports the results of a study of the ‘over‐training’ of apprentices by large manufacturers in the UK. The term ‘over‐training’ was traditionally used to refer to the way in which nationalised industries trained more apprentices than they needed, with the ‘surplus’ being released at the end of their training to find another employer. In contrast, the evidence reported in this article indicates that over‐training now typically involves large employers helping to train apprentices who are employed and paid by other firms from the outset. The project examines the extent and nature of over‐training, the reasons why employers become involved in over‐training, and policy implications. The evidence suggests that over‐training can increase the number of high‐quality apprenticeships. Large employers need to be made more aware of over‐training. Government can help promote over‐training via its ‘Catapult Centres’.     

The economic impact of migration: productivity analysis for Spain and the UK

Over the past 20?years labour has become increasingly mobile and whilst employment and earnings effects in host countries have been extensively analysed, the implications for firm and industry performance have received far less attention. This paper explores the direct economic consequences of immigration on host nations?? productivity performance at a sectoral level in two very different European countries, Spain and the UK. Whilst the UK has traditionally seen substantial immigration, for Spain the phenomenon is much more recent. Our findings from a growth accounting analysis show that migration has made a negative contribution to labour productivity growth in Spain and a negative but negligible contribution in the UK. This difference is driven by a positive impact from migrant labour quality in the UK. This finding broadly holds across all sectors, but we note considerable variation in magnitudes. Labour productivity growth has a neutral contribution from migrant labour in construction and personal services in the UK, whilst in every case in Spain the effect is negative, most strongly in agriculture. Using an econometric approach to production function estimation we observe a positive long term effect on total factor productivity from migrant workers in the UK and a negative effect in Spain. Our findings suggest that either the UK is better at assimilating migrants or is more selective in terms of who is permitted to migrate.     

On typical characteristics of economic time series and the relative qualities of five autocorrelation tests

In an article by L'Esperance and Taylor (1975) some tests against autocorrelation in the linear model are compared by considering their powers in a number of cases. The conclusions are wrong because of two facts: the cases to which the tests were applied are irrelevant and some of the calculations are incorrect. In the present article the relevant field of application is analyzed and correct power calculations are carried out, leading to quite different conclusions.     

Estimation of the Pareto law from underreported data: A further analysis

Estimation of parameters of the Pareto income distribution is discussed for the situation when data are underreported, i.e., observed with negative random bias. Specifically it is proved that maximum likelihood estimates are consistent and asymptotically normal in large samples, and formulae for the large-sample standard errors are given. The large-sample theory illustrates how some important results from mathematical statistics apply to non-standard statistical models.