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The purpose of this paper is to examine the factors influencing defaults and exits from public works by prime contractors of small and medium-sized enterprises in the Japanese construction industry. By analysing the data for several years as panel data, this study determines the extent of influence of changes in company characteristics on the defaults and exits.

Using construction company evaluation (Keiei Jikou Sinsa or Keisin) data and by employing the panel binary logit random effect model, this study empirically analyses the construction industry.

This study shows that defaulting and exiting companies have different characteristics. The result shows financial performance indicators, non-financial performance indicators and Keisin scores to significantly affect defaults and exits. In particular, this study finds non-financial performance indicators, such as whether a firm draws insurance, to significantly affect its likelihood to default or exit and the influence varies on the basis of insurance type.

The feature of this study is that its analysis focuses not only on defaulting companies but also on exiting companies, defined as those that stop operating as prime contractors for public works but otherwise stay in business. In contrast to existing research, this study distinguishes between defaults and exits and analyses the factors that influence a firm following one of these two outcomes. Moreover, although Keisin data are usually used to determine whether companies qualify to enter bids for public works, they can be applied for an attribution analysis of corporate defaults and exits.

The purpose of this paper is to explore the developments in final electricity consumption, estimate the portions of changes that can be attributed to national, sectoral or regional factors, and to investigate determinants of the regional component (RC) in Croatia at the subnational level in the period 2001-2013.

In the first stage, the dynamic shift-share method is used to decompose final electricity consumption, and then, in the second stage, the panel population-averaged logit model is conducted to find the main determinants of the extracted RC.

The results show that both the sectoral factor and the regional factor are responsible for an increase in electricity consumption over the period considered, whereby the regional specificities had a larger impact in general. Thereby, the most developed regions, including the tourism-oriented ones, exhibited the largest average increase in electricity consumption mainly due to positive effects of the regional-specific factors, while the negative effects of these factors were mainly responsible for low average rates of changes in electricity consumption in less developed regions.

The results suggest that regional-specific energy conservation programs might be more effective in improving energy efficiency than the sector-oriented ones, as well as that socio-economic and contextual determinants matter when it comes to the probability of having a positive regional effect on the electricity consumption rate.

The paper investigated the determinants of the extracted RC which has not yet been addressed in the energy economics literature.

The article investigates the patterns of asset impairment recognition in search of signs of “big bath” earnings management practices across an internationally diversified sample of public companies. It also elucidates the incentives that may underlie such practices and explores possible safeguards embedded in the existing corporate governance mechanisms.

The article applied static panel and binary logit models to an international firm-level panel dataset of 1045 public companies observed between 2003 and 2018.

Our empirical results suggest that recognition of asset impairment has no determinate impact on earnings volatility. Investigating the possibility of “big bath” earnings management practices, the authors found no impact of asset impairment recognition on total senior executive compensation in firms, which pay performance-based remuneration. The quality of corporate governance has appeared to impact the firms’ intertemporal proclivity to recognize asset impairment with those having the more entrenched and management-controlled boards being more likely to time impairment recognition by delaying it during exceptionally good and exceptionally bad years. While generally unlikely, recognition of asset impairment in a period with a recorded negative operating performance is found to be closely associated with key executive departures.

The article corroborates the salient role of corporate governance mechanisms in shaping the intertemporal patterns of asset impairment recognition. The possible remedies to the phenomenon should be derived therefrom.

The purpose of this study is to examine whether PV uptake is associated with key housing market determinants and linked to socio-economic profiles. An abundance of extant literature has examined the role of solar photovoltaic (PV) adoption and user costs, with an emerging corpus of literature investigating the role of the determinants of PV uptake, particularly in relation to the built environment and the spatial variation of PV dependency and dissimilarity. Despite this burgeoning literature, there remains limited insights from the UK perspective on housing market characteristics driving PV adoption and in relation spatial differences and heterogeneity that may exist.

Applying micro-based data at the Super Output Area-level geography, this study develops a series of ordinary least squares, spatial econometric models and a logistic regression analysis to examine built environment, housing tenure and deprivation attributes on PV adoption at the regional level in Northern Ireland, UK.

The findings emerging from the research reveal the presence of some spatial clustering and PV diffusion, in line with several existing studies. The findings demonstrate that an urban-rural dichotomy exists seemingly driven by social interaction and peer effects which has a profound impact on the likelihood of PV adoption. Further, the results exhibit tenure composition and “economic status” to be significant and important determinants of PV diffusion and uptake.

Housing market characteristics such as tenure composition across local market structures remain under-researched in relation to renewable energy uptake and adoption. This study examines the role of housing market attributes relative to socio-economic standing for adopting renewable energy.

We examine the roles of sample initial conditions and unobserved individual effects in consistent estimation of the dynamic binary response panel data model. Different specifications of the model are estimated using female welfare and labor force participation data from the Survey of Income and Program Participation. These include alternative random effects (RE) models, in which the conditional distributions of both the unobserved heterogeneity and the initial conditions are specified, and fixed effects (FE) conditional logit models that make no assumptions on either distribution. There are several findings. First, the hypothesis that the sample initial conditions are exogenous is rejected by both samples. Misspecification of the initial conditions results in drastically overstated estimates of the state dependence and understated estimates of the short- and long-run effects of children on labor force participation. The FE conditional logit estimates are similar to the estimates from the RE model that is flexible with respect to both the initial conditions and the correlation between the unobserved heterogeneity and the covariates. For female labor force participation, there is evidence that fertility choices are correlated with both unobserved heterogeneity and pre-sample participation histories.

Research on strategic choices available to the firm are often modeled as a limited number of possible decision outcomes and leads to a discrete limited dependent variable. A limited dependent variable can also arise when values of a continuous dependent variable are partially or wholly unobserved. This chapter discusses the methodological issues associated with such phenomena and the appropriate statistical methods developed to allow for consistent and efficient estimation of models that involve a limited dependent variable. The chapter also provides a road map for selecting the appropriate statistical technique and it offers guidelines for consistent interpretation and reporting of the statistical results.

This study uses cross-border mergers as a test of the ability of foreign directors to provide effective strategic advising. We find that firms with foreign directors on their boards are more likely to engage in cross-border mergers, pursue a higher number of cross-border mergers, and invest more in those mergers. We further determine that firms with foreign directors are more likely to undertake nondiversifying mergers, enjoy friendly mergers, and acquire privately held targets. Moreover, we find that firms with foreign directors have higher announcement period returns and pay less for their cross-border targets.

The purpose of this paper is to examine the factors that affect the discontinuance of business of start-up contractors and property companies in Japan. It will help managers of start-up contractors and property companies to effectively manage their companies. Furthermore, it will be useful for stakeholders with links to start-up companies to analyse the credit risks associated with these businesses.

This study uses data from the Japan Finance Corporation Business Startup Panel Survey to empirically examine the factors that affect the discontinuance of business of start-up companies. A binary logit model is used as the statistical method. Utilising the resource-based view theory, this study explores the relationships between resources and company capabilities at both start-up and discontinuance of business.

Start-up contractors tend to discontinue their business, as managers grow older and when a sufficient workforce cannot be found at start-up. On the other hand, start-up property companies tend to discontinue business when securing of orderers is not sufficient at start-up.

This study analyses start-up contractors and property companies and finds that factors that affect the discontinuance of business differ across construction and property industries, with each industry facing important, sector-specific issues.

This chapter develops a framework for quantile regression in binary longitudinal data settings. A novel Markov chain Monte Carlo (MCMC) method is designed to fit the model and its computational efficiency is demonstrated in a simulation study. The proposed approach is flexible in that it can account for common and individual-specific parameters, as well as multivariate heterogeneity associated with several covariates. The methodology is applied to study female labor force participation and home ownership in the United States. The results offer new insights at the various quantiles, which are of interest to policymakers and researchers alike.

Presents results from cross‐section and conditional logit models estimating the probability of participation by married women. One version of each specification uses potential experience and the other a measure of the number of years worked in the market since the age of 18. A series of cross‐section logit models, representing a threshold analysis of the decision to work in the market, appears to be inappropriate, when unmeasured characteristics influence the probability of participation. Hence, reports results from a conditional logit model controlling for fixed effects. These results confirm the cross‐section findings regarding the limitation of potential experience. The results suggest that potential experience reflects the negative effects of ageing on the probability of participation rather than the positive impact of training or tastes for market work.