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.     

Environmental,social, and governance practices and perceived tail risk

Using the implied volatility smirk on individual equity securities to measure perceived tail risk, we find that better environmental, social and governance (ESG) practices significantly reduce ex-ante expectations of a left-tail event. Our findings are robust to using multiple model specifications and to adjusting for potential endogeneity concerns. We also show that, while practices in each ESG pillar are important in reducing perceived tail risk, the environmental pillar plays the most important role. Our results indicate that investors consider strong ESG practices to be insurance against left-tail events rather than wasteful investment borne out of managers’ own values or self-interest.     

Competition and Appraisal Inflation

The Journal of Real Estate Finance and Economics - In mortgage debt contracts, real property serves as collateral and the terms of mortgage financing are largely conditional on the certification of...     

Modern Slavery and the Discursive Construction of a Propertied Freedom: Evidence from Australian Business

Journal of Business Ethics - This paper examines the ethics of the Australian business community’s responses to the phenomenon of modern slavery. Engaging a critical discourse approach, we...     

Lost and found: Individual differences in propensity to process visual elements of persuasion

Visual processing style, defined as the relative propensity to engage in visual processing rather than verbal processing, is an individual difference variable that has been frequently investigated in the consumer psychology literature. Surprisingly, numerous studies have reported no relationship between visual processing style and viewer responses to visual elements of persuasion. We argue that this accumulation of null results is due to untenable historical theoretical assumptions that underlie the construct, along with methodological problems that are inevitably brought about by those theoretical assumptions. We reconceptualize visual processing style and test an alternative empirical operationalization of it. Using both new data and a reanalysis of data published in the Journal of Consumer Research, we find the old approach yields null results, but we find the new approach yields the expected results. The new approach reinstates the utility of incorporating propensity to engage in visual processing as an individual difference variable into consumer psychology models of visual persuasion, and it reinstates a powerful individual difference variable that can help push forward the investigation of the unique aspects of visual persuasion.     

The Differential Impact of IFRS Adoption on Aspects of Seasoned Equity Offerings in the UK and France

We examine the potential for IFRS to influence the market for SEOs in the UK and France. The divergence between the UK domestic accounting standards and IFRS is minor (low-divergence firms) whereas domestic accounting standards in France differ materially from IFRS (high-divergence firms); however, both countries have similar legal enforcement and institutional settings that might confound the effect of IFRS adoption. We argue that IFRS adoption serves to mitigate information asymmetry and improve accounting quality. Accordingly, we find that, following IFRS adoption, earnings management activities decrease among high-divergence firms prior to issuing SEOs. As a result of the lower levels of earnings management and information asymmetry, we predict and find that the market reaction to issuing SEOs improves significantly for high-divergence firms following IFRS. Given that equity financing becomes less costly, we find that the propensity to issue new SEOs increases among high-divergence firms after IFRS adoption. We find no similar changes among low-divergence firms. The results persist after running a matched-sample analysis and controlling for potential self-selection bias.     

Peer effects in the diffusion of water‐saving agricultural technologies

We investigate the role of peer effects in the diffusion of an important water‐saving irrigation technology: low energy precise application (LEPA). Using detailed irrigation behavior data for growers in the High Plains Aquifer region of Kansas covering 1990–2014, we find clear evidence of peer influence in adoption of LEPA, net of environmental factors. Specifically, an additional neighboring LEPA installation within 1 km increases the probability of adoption by about 0.3 percentage points, on average, and this effect diminishes with distance. Our empirical estimates indicate that in the absence of peer effects, LEPA adoption would have been about 10% lower (1,000–1,600 fewer installations) per year. In addition, we find that growers install LEPA in response to higher energy prices.     

When does economic model type become a decisive factor in health technology appraisals? Learning from the expanding treatment options for relapsing–remitting multiple sclerosis

Objectives: Specific economic model types often become de facto standard for health technology appraisal over time. Markov and discrete event simulation (DES) models were compared to investigate the impact of innovative modeling on the cost-effectiveness of disease-modifying therapies (DMTs) in relapsing–remitting multiple sclerosis (RRMS). Fingolimod was compared to dimethyl fumarate (DMF; in highly active [HA] RRMS), alemtuzumab (in HA RRMS) and natalizumab (in rapidly evolving severe RRMS). Comparator DMTs were chosen to reflect different dosing regimens.

Materials and methods: Markov and DES models used have been published previously. Inputs were aligned in all relevant respects, with differences in the modeling of event-triggered attributes, such as relapse-related retreatment, which is inherently difficult with a memoryless Markov approach. Outcomes were compared, with and without different attributes.

Results: All results used list prices. For fingolimod and DMF, incremental cost-effectiveness ratios (ICERs) were comparable (Markov: £4206/quality-adjusted life year [QALY] gained versus DES: £3910/QALY gained). Deviations were observed when long-term adverse events (AEs) were incorporated in the DES (Markov: £25,412 saved/QALY lost, versus DES: £34,209 saved/QALY lost, fingolimod versus natalizumab; higher ICERs indicate greater cost-effectiveness). For fingolimod versus alemtuzumab, when relapse-triggered retreatment was included in the DES, large cost differences were observed (difference between incremental cost is £35,410 and QALY is 0.10).

Limitations: UK payer perspective, therefore societal approach was not considered. Resource utilization and utilities for both models were not derived from the subpopulations; as the focus is on model type, input limitations that apply to both models are less relevant.

Conclusions: Whilst no model can fully represent a disease, a DES allows an opportunity to include features excluded in a Markov structure. A DES may be more suitable for modeling in RRMS for health technology assessment purposes given the complexity of some DMTs. This analysis highlights the capabilities of different model structures to model event-triggered attributes.     

Rural school access and the agricultural transformation

Improving children's access to primary and secondary education is a strategic goal for many global development agencies and government policymakers. Nevertheless, there is relatively little research examining how changes in rural school supply affect future labor markets. We leverage variation in the timing and location of secondary school construction in Southern Mexico to identify the effects of school supply on labor outcomes. We find that school construction increases expected education for school-aged children by about 4 years and raises the share of years working in the nonagricultural sector between the ages of 18–22 by 29.8 percentage points. The magnitude of the effects on share of years doing nonagricultural work is smaller for individuals from homes where an indigenous language is spoken. Our findings indicate that rural school construction in less-developed countries can accelerate the transformation from agricultural to nonagricultural economies, but there may be heterogeneous effects across socioeconomic groups and ethnicities.