A sequential Monte Carlo approach to inference in multiple‐equation Markov‐switching models

Vector autoregressions with Markov‐switching parameters (MS‐VARs) offer substantial gains in data fit over VARs with constant parameters. However, Bayesian inference for MS‐VARs has remained challenging, impeding their uptake for empirical applications. We show that sequential Monte Carlo (SMC) estimators can accurately estimate MS‐VAR posteriors. Relative to multi‐step, model‐specific MCMC routines, SMC has the advantages of generality, parallelizability, and freedom from reliance on particular analytical relationships between prior and likelihood. We use SMC's flexibility to demonstrate that model selection among MS‐VARs can be highly sensitive to the choice of prior.     

All grown up? The fate after 15 years of a quarter of a million UK firms born in 1998

The theory of firm growth is in a rather unsatisfactory state. However, the analysis of large firm-level datasets which have become available in recent years allows us to begin building an evidence base which can, in turn, be used to underpin the development of more satisfactory theory. Here we study the 239 thousand UK private sector firms born in 1998 over their first 15 years of life. A first, and quite striking, finding is the extraordinary force of mortality. By age 15, 90% of the UK firms born in 1998 are dead, and, for those surviving to age 15, the hazard of death is still about 10% a year. The chance of death is related to the size and growth of firms in an interesting way. Whilst the hazard rate after 15 years is largely independent of size at birth, it is strongly affected by the current (age 14) size. In particular, firms with more than five employees are half as likely to die in the next year as firms with less than five employees. A second important finding is that most firms, even those which survive to age 15, do not grow very much. By age 15 more than half the 26,000 survivors still have less than five jobs. In other words, the growth paths – what we call the ‘growth trajectories’ – of most of the 26,000 survivors are pretty flat. However, of the firms that do grow, firms born smaller grow faster than those born larger. Another striking finding is that growth is heavily concentrated in the first five years. Whilst growth does continue, even up to age 15, each year after age five it involves only a relatively small proportion of firms. Finally, there are two groups of survivors which contribute importantly to job creation. Some are those born relatively large (with more than 20 jobs) although their growth rate is quite modest. More striking though, is a very small group of firms born very small with less than five jobs (about 5% of all survivors) which contribute a substantial proportion (more than one third) of the jobs added to the cohort total by age 15.     

Comparing automated text classification methods

Online social media drive the growth of unstructured text data. Many marketing applications require structuring this data at scales non-accessible to human coding, e.g., to detect communication shifts in sentiment or other researcher-defined content categories. Several methods have been proposed to automatically classify unstructured text. This paper compares the performance of ten such approaches (five lexicon-based, five machine learning algorithms) across 41 social media datasets covering major social media platforms, various sample sizes, and languages. So far, marketing research relies predominantly on support vector machines (SVM) and Linguistic Inquiry and Word Count (LIWC). Across all tasks we study, either random forest (RF) or naive Bayes (NB) performs best in terms of correctly uncovering human intuition. In particular, RF exhibits consistently high performance for three-class sentiment, NB for small samples sizes. SVM never outperform the remaining methods. All lexicon-based approaches, LIWC in particular, perform poorly compared with machine learning. In some applications, accuracies only slightly exceed chance. Since additional considerations of text classification choice are also in favor of NB and RF, our results suggest that marketing research can benefit from considering these alternatives.     

Oil shocks and volatility jumps

Review of Quantitative Finance and Accounting - In this paper, we analyse the role of oil price shocks, derived from expectations of consumers, economists, financial market, and policymakers, in...     

The Brexit effect: the case of UK ADR performance one year later

In an unexpected outcome, UK voters decided that it was time to exit the European Union based on the results of a vote held on 23 June 2016. Studies of the affects and implication of Brexit include a study showing that the vote was met with a negative short-term wealth effect for UK American depository receipts (ADRs). This study examines the one-year anniversary holding period returns of these ADRs along with the British Pound and the FTSE 100 to discover any lingering effects from the historical vote. Results indicate that the one-year holding period returns for the ADRs averaged 5.8% for the year while the FTSE gained 4.8%, the S&P 500 gained 15.4% and the Pound lost 13.2% of its value.     

Discretionary technology bootlegging tensions in institutional healthcare work

We explore individuals who take some of their technology use ‘underground’, described as ‘bootlegging’, to enhance healthcare work. We find that healthcare professionals’ informal use of mobile applications in healthcare work sometimes ‘sticks out’ and this produces professional identity tensions: (1) conflict with perceptions of professional behaviour, and (2) defilement of expert judgment. Our analysis, moreover, reveals that identity work (i.e. ‘accepting’ and ‘sensemaking’) provides a coping mechanism to deal with these unresolved professional identity tensions. This paper contributes to a better understanding of the constitutive entanglements and two‐way interactions of discretionary technology bootlegging, professional identity and autonomy in institutional healthcare work.     

Agency costs and tax planning when the government is a major Shareholder

In state owned enterprises (SOEs), taxes are a dividend to the controlling shareholder, the state, but a cost to other shareholders. We examine publicly traded firms in China and find significantly lower tax avoidance by SOEs relative to non-SOEs. The differences are pronounced for locally versus centrally-owned SOEs and during the year of SOE term performance evaluations. We link our results to managerial incentives through promotion tests, finding that higher SOE tax rates are associated with higher promotion frequencies of SOE managers. Our results suggest managerial incentives and tax reporting are conditional on the ownership structure of the firm.     

The response of asset prices to monetary policy shocks: Stronger than thought

Standard macroeconomic theory predicts rapid responses of asset prices to monetary policy shocks. Small‐scale vector autoregressions (VARs), however, often find sluggish and insignificant impact effects. Using the same high‐frequency instrument to identify monetary policy shocks, we show that a large‐scale dynamic factor model finds overall stronger and quicker asset price reactions compared to a benchmark VAR, both on euro area and US data. Our results suggest that incorporating a sufficiently large information set is crucial to estimate monetary policy effects.     

An anatomy of zero‐hour contracts in the UK

We present the first attempt to locate zero‐hour contract (ZHC) jobs—jobs that lack a guaranteed minimum number of hours—within theoretical frameworks of the employment relationship and occupational class and empirically explore their characteristics using successive UK Labour Force Survey. In line with these theories, we find this contentious form of employment to be strongly differentiated by the nature of occupational tasks and to overlap with nonstandard employment features (e.g. part‐time and temporary). They are also highly concentrated in a small number of occupations and sectors, with over half of ZHC jobs found in just 10 occupations. We further show that ZHCs are associated with indicators of inferior job quality such as low pay and underemployment. Although we find no evidence that ZHCs are a particularly pervasive feature of the UK labour market, further growth cannot be ruled out in certain occupations.     

Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?

This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.