Change-point analysis through integer-valued autoregressive process with application to some COVID-19 data

In this article, we consider the problem of change-point analysis for the count time series data through an integer-valued autoregressive process of order 1 (INAR(1)) with time-varying covariates. These types of features we observe in many real-life scenarios especially in the COVID-19 data sets, where the number of active cases over time starts falling and then again increases. In order to capture those features, we use Poisson INAR(1) process with a time-varying smoothing covariate. By using such model, we can model both the components in the active cases at time-point t namely, (i) number of nonrecovery cases from the previous time-point and (ii) number of new cases at time-point t. We study some theoretical properties of the proposed model along with forecasting. Some simulation studies are performed to study the effectiveness of the proposed method. Finally, we analyze two COVID-19 data sets and compare our proposed model with another PINAR(1) process which has time-varying covariate but no change-point, to demonstrate the overall performance of our proposed model.     

Schooling, Informal Experience, and Formal Sector Earnings: A Study of Indian Workers

This paper estimates an earnings function for male workers belonging to the Indian corporate sector. The model allows for differential rates of return to schooling and distinguishes tenure from total labor market experience. The rate of return to schooling is found to be low up to the junior level, increases significantly at the secondary and undergraduate levels, but sharply declines at the masters level. Seniority and firm-specific factors are found to be important determinants of earnings. When years of unemployment and informal experience are incorporated, earnings of low-education workers appear to be driven entirely by formal-sector experience.     

Estimating Nested Count Data Models

Count data models have found a wide variety of applications not only in applied economics and finance but also in diverse fields ranging from biometrics to political science. Poisson and negative binomial (NB) models have been extensively used in count data analysis. Two particular NB model specifications, NBI and NBII, have been especially popular. However, these models impose arbitrary restrictions on the relation between the conditional mean and variance of the dependent variable, limiting their generality. This study proposes tests for selection among the Poisson and NB models by formally demonstrating that the log likelihood function (LLF) of a general NB model parametrically nests the LLF of the Poisson, NBI and NBII as testable special cases. It also proposes estimation of the general NB model since it allows greater flexibility in the relationship between the mean and variance of the dependent variable than NBI and NBII. The empirical application, which uses micro-level data on recreational boating, provides support for the paper's main theme. Tests clearly reject not only the Poisson, but also NBI and NBII, in favour of a different NB model, underscoring the importance of the general model specification.     

Policy analysis for growth of a new technology product

Three important aspects of the growth of a new technology product are new product diffusion, rise in productivity, and new product management. The authors maintain that these three aspects are interrelated. The study presented in this paper selected a system dynamics framework to address, in a unified fashion, the above-mentioned aspects of growth in the context of the TV industry in India. The study indicates that (a) in conformity to the present trend, new product diffusion should be treated as a multiattribute phenomenon, and a study of causal factors and their relationships hold the key to understanding this phenomenon, (b) contrary to the prevailing belief, new technology may not enhance capital or total productivity, particularly after the end of the major expansion phase of the product life cycle, and (c) new product growth is generally associated with a loss of market share during the major growth phase and an overcapacity at the end of this phase. Various policy tests on the model reveal that in the case of the Indian TV industry, employee skill has the highest leverage in improving company performance in terms of increased market share, increased productivity and profitability figures, and reduced overcapacity.     

Implementing circular economy in the textile and clothing industry

This research reveals the current state of the circular economy (CE), challenges and opportunities of implementing CE and interventions that could facilitate effective implementation of CE in the textile and clothing (TC) industry. The study uses a survey method within 114 TC companies based in Bangladesh, Vietnam and India revealing the correlation of CE fields of action (take, make, distribute, use and recover) with sustainability (economic, environmental and social) performance. The lack of financial, technological and human resources along with management's reluctance and end-user's indifference to sustainability is the biggest challenge for CE implementation. The research further derives that the TC firms are unable to eradicate the challenges to CE implementation without a holistic approach that involves the collective effort from the industry, host government's incentives, their buyers and above all the conscience of the end-users. Finally, the study reveals that the collaborative efforts, knowledge sharing in sustainability management across the value chain and marketisation of the waste recycling, among others, are a few actions the stakeholders of the TC industry must adopt for implementing CE successfully.     

Drop-the-loser design in the presence of covariates

In the present work we develop a randomized two-treatment adaptive allocation design with covariates ensuring smaller variability of treatment allocations. We study, both numerically and theoretically, several exact and limiting properties of the design and consider an inferential problem following the allocation design. We compare the design with some of the existing allocation designs by computing its various performance measures.     

Impact of traffic citations to reduce truck crashes on challenging roadway geometry

Wyoming's Interstate 80 has one of the highest truck crash rates in the United States. This is due to a variety of reasons, including high percentage of truck traffic, adverse weather conditions and mountainous terrain. These factors have caused the Wyoming Highway Patrol (WHP) to spend extensive resources on inspecting commercial vehicles and enforcement of traffic laws in this corridor. This study estimated the correlation between traffic citations and truck crashes. In addition, the paper evaluated the increased risk of truck crashes in adverse weather and road conditions. The explanatory variables included geometric features, weather condition, traffic volume and types of citations. This research concluded that speeding related citations and truck crashes are negatively correlated, and the risk of truck crashes is significantly higher when weather is not clear, and the road is not dry.     

Join hands or walk alone? Evidence on lobbying for trade policy in India

Using primary evidence for 146 Indian manufacturing firms, I examine single and dual lobbying strategies for trade policy influence, and the factors driving firm's choice of these strategies. Firms can adopt a single strategy, by lobbying collectively as a group (Join Hands), or lobbying individually as a firm (Walk Alone). Firms can also adopt a dual strategy, that is, a combination of collective and individual lobbying. The choice of strategy is affected by sector concentration and by tradeoffs between lobbying intensity for sector‐wide and firm‐specific outcomes. The following findings are new for India: First, majority of Indian firms (more than 64% in the sample) use a dual strategy, suggesting the importance to better understand what drives dual strategies. Second, the likelihood of adopting a dual lobbying is higher in sectors that are characterized by low concentration (dispersion is higher), indicating a strong competition effect over free‐riding. Third, relative to the single strategy of collective lobbying, Indian manufacturing firms are likely to join hands while walking alone when targeting firm‐specific outcomes, but prefer to walk alone (single strategy of individual lobbying) when there are tradeoffs between different outcomes, to react quickly. Finally, the availability of resources and firm's perceived effectiveness of its lobbying are significant drivers for the strategy choice.     

Drivers of technical efficiency in Malaysian banking: a new empirical insight

Restructuring and rationalisation of Malaysian banking in 2000 and the subsequent policy of deregulation and liberalisation adopted by Bank Negara Malaysia (BNM) have resulted in a significant transformation of Malaysian banking. Banks are now poised to play a pivotal role in the economic transformation of the economy as envisaged in the Financial Sector Blue Print 2011–20 of BNM. Using the data envelopment analysis technique, the technical efficiency of 19 commercial banks (8 domestic banks and 11 foreign banks) operating in Malaysia during 2005–12 is evaluated. Then, using bootstrap‐corrected efficiency scores, the drivers of bank efficiency were estimated using the Tobit regression approach. Results clearly show that three large domestic banks are not only more efficient than their counterparts, but are also more efficient than the foreign banks. Bank size and return on assets are found to be the significant drivers of technical efficiency of Malaysian banks. Capital adequacy and the advances to deposit ratio also have a role in driving technical efficiency. The results also indicate that banks that are more effective in managing credit risk, as reflected in a lower level of non‐performing assets as a percentage of total assets, and have lower levels of personnel expenses to total assets, are more efficient. The findings have significant implications at the individual bank level and also at the policy level.     

The Value Relevance of Corporate Social Responsibility Expenditure: Evidence from Regulatory Decisions

We examine the value relevance of the corporate social responsibility (CSR) expenditure of Bangladeshi banks from 2007–2014 in response to a regulatory directive on banking firms’ engagement in CSR activities. We find a positive association between CSR expenditure and a firm's market value. Evidence of an inverse U-shaped curvilinear association between CSR expenditure and market value suggests that the impact of CSR expenditure on a firm's market value has a certain limit. We also document that unexpected or abnormal components of CSR expenditure comprise value-relevant information. Our study provides empirical evidence to support the value relevance of CSR expenditure as an explanation for why firms should invest in CSR and why they should inform various stakeholders about their CSR activities.