Inverse Mills Ratio Research Articles

Digital finance and MSME performance in India: evidence from World Bank Enterprise Survey data

PurposeThe impact of digitalisation on smaller firms remains sparsely studied across emerging economies. The paper aims to examine the relationship between digital adoption and multiple performance parameters of micro, small and medium enterprises (MSME) in a prominent emerging economy.Design/methodology/approachThe study employs data from the World Bank Enterprise Survey (WBES) 2022, capturing 9,024 Indian MSME firms spread across the country. Performance indicators are derived from growth in sales, employment and labour productivity (LPROD). Multiple regression estimates are derived that also correct for sample selection bias using Heckman’s two-step process.FindingsDigital proliferation is found to increase as firms mature up in terms of age, size and constitution. A significant difference could also be observed in business performance across digital and non-digital businesses, with sales growth (SG) and productivity higher for digital firms. Digital financial variables are found to have a significant impact on SG but not as much in the case of employment growth and LPROD. The results are robust to correction for sample selection bias in digital adoption using inverse mills ratio (IMR).Practical implicationsThe study highlights digital adoption gaps across various strata of MSMEs, highlighting lower adoption when firms are younger, smaller and lacking formal constitutional setup. Digital variables indicating positive association with SG highlight the need for concerted efforts at the public policy level for building appropriate skills and infrastructure for micro and small enterprises to boost their digital adoption to promote growth.Originality/valueThere is a lack of micro-level empirical evidence measuring the impact of advanced digital technology usage on multiple aspects of enterprise performance amongst micro and small firms. The study deploys unique digital variables including TReDS and use of online credit applications to assess the impact on business performance. The findings provide insights for practice and public policy, besides making the case for a higher focus on launching digital initiatives for smaller enterprises.

Ownership share in cross-border acquisitions: does high-tech status of the target matter?

PurposeThe purpose of this study is to investigate the influence of the target firm’s high-tech status on the share of ownership decision in cross-border acquisitions (CBAs), which is an under-explored topic in cross-border M&A literature.Design/methodology/approachThe authors used Tobit regression and tested the hypotheses using a sample of 7,011 CBA transactions between 1999 and 2014. Inverse Mills ratio was used to address selection bias, and various robustness tests were performed.FindingsThe authors found that acquirers seek greater ownership share when acquiring high-tech firms, and that this relationship is moderated by various firm and national level factors. Specifically, the positive relationship between the high-tech status of a target firm and ownership share acquired is stronger when the firms’ primary operations are highly related or there is high formal institutional distance between the firms’ home countries, but it is weaker when acquirers have more prior M&A experience or there is high cultural and geographic distance between the firms’ home countries.Originality/valueWhile the topic of ownership strategy in CBAs is advancing, it is still limited, especially when examining acquisitions of high-tech target firms. The authors contribute to the research on CBAs and ownership strategy by focusing on the high-tech status of the target firm, and using a sample of both private and public target firms from 116 countries.

The Benefits of Cross-Border Corporate Venture Capital Investment on the Likelihood of a Venture Firm’’s IPO

Purpose - Extant research indicates that CVC investments create value for venture firms and generally enhance the likelihood of a successful venture exit. In particular, despite the globalization of CVC investments, the impact on venture firm exit performance has been largely overlooked. Thus, this study explores the impact of cross-border CVC investments on the likelihood of a venture firm’s IPO. We argue that the foreignness of CVCs increases the likelihood of IPO, but this positive relationship is weakened when CVC units have a tight structure.
 Design/Methodology/Approach - The hypotheses are tested with 1,874 high-technology venture firms in the U.S. that received CVC investments between 1994 and 2009. A two-stage analysis was employed to address potential selection bias. In the first stage, we employed a probit model to predict the probability of receiving cross-border CVC investment. In the second stage, we conducted a probit regression analysis on the likelihood of IPO, incorporating the inverse Mills ratio to address selection bias.
 Findings - We found that the foreignness of CVCs increases the likelihood of a venture firm’s IPO. However, this positive impact is weakened when CVCs have a tight governance structure.
 Research Implications - This study highlights the benefits of cross-border CVC investments and enriches resource dependence theory by reconciling it with institutional theory, depicting the importance of both reducing resource constraints to create value for venture firms and the institutional logic pursued by CVCs. This study suggests that entrepreneurs should be careful with CVC units that prioritize strategic objectives.

Has increased prominence of translation results changed net investment hedging practice?

PurposeThe purpose of this paper is to examine the impact of greater reporting prominence of translation results following Accounting Standard Update (ASU) 2011-05 on net investment (NI) hedging practice. The authors investigate the role of increased transparency on the decision to engage in NI hedging (participation), the degree of NI hedging (level) and the hedging vehicle choice.Design/methodology/approachThis paper uses the Heckman two-stage procedure (Heckman, 1979) in the hedging choice analysis. In the first stage, the authors model the participation decision as a function of reporting transparency, translation results and other control variables. In the second stage, the authors include the Inverse Mills ratio from the first stage Probit to examine both the level and vehicle choice decisions.FindingsWhen translation is reported more prominently, the authors find an increase in the level of NI hedging and a greater likelihood of debt as the hedging vehicle, but no evidence firms are more likely to hedge. Regardless of where translation results are reported, firms facing ongoing translation losses are more likely to hedge.Research limitations/implicationsThis paper examines S&P 500 firms in the years surrounding the effective date of ASU 2011-05. The findings suggest managers respond to the increase in reporting transparency by increasing hedging for long-term risk management purposes, supporting accounting authorities’ efforts to promote other comprehensive income information transparency. The results should hold for comparable firms with similar currency exposure, size and visibility, but may not apply to smaller firms with limited translation exposure. As only about a quarter of firms with translation exposure engage in NI hedging, the primary results are based on a relatively limited number of firms.Originality/valueTo the best of the authors’ knowledge, this is the first study that examines NI hedging behavior changes following ASU-2011-05. Second, the authors are the first to explore why firms are almost equally split between derivatives and debt as their exclusive hedging vehicle.

Life's simple 7 and its association with trajectories in depressive symptoms among urban middle-aged adults

BackgroundThe American Heart Association Life's Simple 7 (LS7) is a composite metric assessing cardiovascular health on a scale of 0–14 comprised of nutrition, physical activity, cigarette use, body mass index, blood pressure, cholesterol and glucose. MethodsUsing data from the Healthy Aging in Neighborhoods of Diversity across the Life Span study [n = 1465, Age at visit 1 (v1: 2004–2009): 30–66 y, 41.7 % male, 60.6 % African American], we investigated associations of trajectories in depressive symptoms (2004–2017) with Life's simple 7 scores after ∼8.6 years follow-up (2013–2017). Analyses used group-based zero-inflated Poisson trajectory (GBTM) models and multiple linear or ordinal logistic regression. GBTM analyses generated two classes of depressive symptoms trajectories (“low declining” and “high declining”), based on intercept and slope direction and significance. ResultsOverall, “high declining depressive symptoms” vs. the “low declining” group was associated with −0.67 ± 0.10 lower scores on LS7 total score (P < 0.001) in analyses adjusted for age, sex, race and the inverse mills ratio. This effect was markedly attenuated to −0.45 ± 0.10 score-points (P < 0.001) upon adjustment for socio-economic factors and to −0.27 ± 0.10 score-points (P < 0.010) in fully adjusted analyses, with a stronger association detected among women (β ± SE: −0.45 ± 0.14, P = 0.002). An association between elevated depressive symptoms over time (“high declining” vs “low declining”) and LS7 total score was detected among African American adults (β ± SE: −0.281 ± 0.131, p = 0.031, full model). Moreover, the “high declining” vs. “low declining” depressive symptoms group was associated with a lower score on LS7 physical activity (β ± SE: −0.494 ± 0.130, P < 0.001). ConclusionsPoorer cardiovascular health was linked to higher depressive symptoms over time.

The Effect of the Use of Solidarity Financing on Entrepreneurial Activities in the North West and South West Regions of Cameroon

This study was focused on investigating the effect of solidarity financing on entrepreneurial activities in the North West and South West regions of Cameroon. The mission of solidarity finance is to use non-conventional financial tools to achieve sustainable and equitable development beside social integration. Its implications are seen in entrepreneurial performance measured by increase business revenue, profit, sales and societal contribution. The paper examines if entrepreneurs who adopt solidarity financing performed better than those who do not use it in the Northwest and Southwest regions of Cameroon. To achieve the objectives of the study, data was collected through survey questionnaire from a sample of 330 respondents and was analyzed using two stage Heckman selection model in order to correct the selection bias and yield unbiased estimates. The results showed that socio-economic factors of accessibility, cultural ties, marital status, age, residence, qualification, development perception services had positive and statistically significant effects on entrepreneurial performance. The coefficient of the inverse Mills ratio from Heckman result was statistically significant at 5%. These results provide evidence that the unobserved factors which lead to an increased probability of usage of solidarity financing have a positive impact on entrepreneurial growth. The government should therefore design policies for the formalization of the solidarity financing market.

A selection bias approach in the circular economy context: The case of organic municipal solid waste in Italy

Organic waste is often indicative of the amount of food waste, and it primarily reflects the consumption habits of households. As underlined by the applicable principles of the Circular Economy (CE), prevention is always the first choice when dealing with waste but evaluating the prevention framework without considering the application of waste separation policies appears to be a complex task. Considering Italian municipal waste management, the implementation of separation policies has been delayed in several provinces. It is difficult to assess the effectiveness of prevention policies established by international and national authorities in this context. The lack of organic waste separation is registered as a missing value in datasets: such instances are often non-random. The research objective of this work is to assess whether economic activity affects organic waste generation and, once the selection bias has been investigated, try to assess the overall implications. Initial findings corroborate the Environmental Kuznets Curve Hypothesis under biased and unbiased estimations. The tipping point is relatively lower when the inverse Mills Ratio is considered, which is positive. Hence, an increase of the expected economic activity requirement could result in a cost that municipalities incur when delaying the enforcement of separation policies. The missing information undermines the potential feedback from practitioners and other stakeholders capable of steering expectations: the unobserved flows have to reach a certain level before being collected.

“Tree to fight hunger”: determinant of enset market participation and intensity of participation: the case of Southwest Ethiopia

Kaffa, Sheka, and Bench sheko Zone in the Southwest region of Ethiopia are known for enset farming. The objective of this study was to identify factors constraining market participation of enset producers and marketed surplus. Data were obtained from a sample of 657 enset producers. Heckman's two-stage model was used to identify the determinants of enset products market participation and marketed surplus. Heckman's two-stage selection model results showed that family size, level of education, farming experience, land allocation, livestock ownership, and access to training had significantly influenced market participation decision while family size, level of education, farming experience, livestock ownership, access to transport, quantity enset produced, off-farm income and inverse Mill's ratio (LAMBDA) influenced significantly the extent of marketed surplus. Based on the findings of the study, we suggest that the government and concerned stakeholders should focus on promoting improved enset variety, encouraging the use of labor-saving technology, strengthening the existing social services, promoting farmers' cooperatives, empowering women, improving market linkage, and competitive market should be created.

Adoption and impact of super granulated urea (guti urea) technology on farm productivity in Bangladesh: A Heckman two-stage model approach

We aimed to determine the impact of farmers’ guti urea technology adoption on farm productivity in the Rajbari District of Bangladesh. The multi-stage sampling techniques were used to obtain a total 400 samples where 181 (45.25%) adopters and 219 (54.75%) non-adopters. The pre-canvassing structured survey schedule was used during the personal interviews. In addition, FGDs and KIIs were conducted to obtain qualitative information. To analyze the collected data, descriptive statistics, probit regression, and Heckman's two-stage model were used. Firstly, a binary regression model was used to examine the factors determining the participation of farmers in the use of guti urea technology. Secondly, treatment effect was assessed by the Heckman's two-stage model to identify the impact of the farmers’ participation on the adoption of guti urea technology. The inverse Mill's ratio coefficient indicates the presence of selection bias and the efficacy of applying the two-stage Heckman model. The results show that the involvement of farmers in the use of guti urea technology has a significantly positive impact on farm productivity. The analysis also shows that a 1% increase in adoption of guti urea technology contributes to a significant increase in farm productivity when other factors remain the same. We conclude that there is room for further increases in farm productivity through planned guti urea technology adoption in crop production. We recommend that the policy makers and authority expand the use and ensure the accessibility of guti urea as well as disseminate knowledge through the development of training opportunities for farmers to increase and enhance the reach of guti urea adoption amongst farmers. The results imply that the provision of complementary services is necessary in addition to the adoption of guti urea to achieve the aim of improving productivity.

A Study on Impact of Farmer Producer Organisation on Farmers’ Income in Andhra Prdesh

The present paper gives the information about the impact of Farmer Producer Organisation on farmers income. The data was collected from both the members of FPO and non- members regarding the socio-economic factors and farming details of farmers. Logistic regression which was a binary regression model was used for determining the factors influencing the farmers to join as group members and then ordinary least square regression was estimated to study the impact of FPOs on farmers income by including inverse mills ratio which was calculated in logistic regression model, to remove the selection bias. The results showed that education, distance to market and age are the factors determining the farmers to join as members of FPO. The impact study results showed that group membership, hired labour, crop production area, share of crop sold and market size are the factors that are positively significant and increasing the farmers income.

Sample selection models with monotone control functions

The celebrated Heckman selection model yields a selection correction function (control function) proportional to the inverse Mills ratio, which is monotone. This paper studies a sample selection model that does not impose parametric distributional assumptions on the latent error terms, while maintaining the monotonicity of the control function. We show that a positive (negative) dependence condition on the latent error terms is sufficient for the monotonicity of the control function. The condition is equivalent to a restriction on the copula function of latent error terms. Using the monotonicity, we propose a tuning-parameter-free semiparametric estimation method and establish root n-consistency and asymptotic normality for the estimates of finite-dimensional parameters. A new test for selectivity is also developed in the presence of the shape restriction. Simulations and an empirical application are conducted to illustrate the usefulness of the proposed methods.

Earnings gap between men and women in the informal labor market in Cameroon

AbstractThis paper investigates the extent of gender earnings gap among informal labor market workers in Cameroon. We have used the 2010 employment and informal sector survey, the Heckman two‐step bivariate selection model, and the Neuman–Oaxaca–Ransom decomposition framework to address these concerns. We find that, compared to men, women are more likely to make the joint decision of participating in the labor market and choosing informal work. Findings also reveal that among informal workers, male workers have an earnings premium over their female counterparts. Returns to informal labor market experience are solidly consistent in narrowing the gender earnings gap. Among the self‐employed workers, male workers also enjoy an earnings premium. However, when the inverse Mills ratio is decomposed, the overall and the self‐employed gender discrimination virtually disappears. Meanwhile, female wage earners enjoy a wage premium and have an unambiguous education‐based advantage over their male counterparts. The implications of these findings support the wisdom that promoting the human capital development of the girl child would play a vital role in alleviating gender‐based differentials by eroding sociocultural conventions and advancing women's agency.

Understanding the determinants of climate change adaptation strategies among smallholder maize farmers in South-west, Nigeria

Climate is one of the most important factors in agricultural productivity, which could directly or indirectly influence productivity since the climate is linked to physiological processes. It is, therefore, essential to understanding the various strategies used by farmers to mitigate the adverse impact of climate change and the factors that influence maize farmers' adoption and intensity of climate change adaptation strategies among smallholder maize farmers in South-west Nigeria. In all, a sample of three hundred and thirty (311) smallholder maize farmers were interviewed. A double-hurdle count data model was employed to estimate the factors influencing farmers' adoption of adaptation strategies while accounting for selection bias with the plugging of inverse mill ratio (IMR) as a regressor. Significant variables such as household size, depreciation ratio, frequency of extension visits, access to extension, and non-farm income were factors influencing the adoption of climate change adaptation strategies among maize farmers. Age of the respondent, age square, household size, farm-based organization (FBO), non-farm income, climate information, access to credit, farmers residing in Osun State (location_Osun), distance to market significantly influenced the intensity of climate change adaptation strategies. This study, therefore, concluded that farm-level policy efforts that aim to improve rural development should focus on farmers’ membership in FBO, increase the visits of extension agents, encourage non-farm income and access to climate change information, particularly during the off-cropping season. Policies and investment strategies of the government should be geared towards supporting improved extension service, providing on-farm demonstration training, and disseminating information about climate change adaptation strategies, particularly for smallholder farmers in Nigeria.

Evaluating rural participation in wetland management: A contingent valuation analysis of the set-aside policy in Iran

Growing conditions of water scarcity and population growth necessitate measures for improved water availability to meet agricultural, industrial, and domestic and consumer water demands; generating new environmental pressures on wetlands and other aquatic ecosystems. In Iran, the “set-aside program” incentivizes farmer participation in wetland conservation through mandated land management practices, making them key stakeholders in environmental conservation action. This study explores attitudes to participation in the set-aside wetland conservation program to revive the Jazmurian wetland in Iran, using a random sample of 226 farmer-stakeholder respondents. Farmers were surveyed to investigate economic and social participation using a willingness to accept (WTA) and willingness to pay (in money per ha) (WTP) model. Results show strong (45%) respondent opposition to wetland conservation participation. On the basis of their WTA, the amount of compensation offered by the villagers was significantly affected by “the cultivated area”, “gender”, “education”, “family size”, “residency”, “income”, “moralism”, and “Inverse Mills Ratio index” factors. Also, “the cultivated area”, “age”, “education”, “marital status”, “family size”, and “income” were found to be significantly affecting their WTP. We argue firstly, that policies to improve wetland conservation must join together infrastructure and agricultural development planning – such that dam projects, agricultural and water conservation planning are better integrated across wetland catchments. Secondly, that wetland conservation participation will be improved through land consolidation agreements for small-holders, and through incomes stabilization, capacity building, social learning and awareness-raising initiatives for farmers towards sustainable agricultural practices.

Bias-corrected State-by-state Forecasts of COVID-19 Deaths

Since testing for COVID-19 infections is not at all randomized over the general population, most epidemiological model forecasts of deaths are subject to `selection bias.' This paper updates and supplements Vinod and Theiss (2020), where the bias correction using generalized linear models (GLM) and inverse mills ratio (IMR) are described in detail. We include state-by-state forecasts using Poisson regression to predict one-week-ahead cumulative deaths from logarithms of current cumulative infections. We hope that the details provided here will help local governors and mayors in their opening up decisions.

Does India do IT? The nexus of IT, skills, organizational factors and productivity

PurposeThe goal of this study is to investigate the nexus among TFP (total factor productivity), IT (information technology) capital accumulation, skills and key plant variables of 34 Indian industries for the period of 2009–2015.Design/methodology/approachAnnual Survey of Industries (ASI) data series are extracted and formulated using Microsoft SQL server. The authors employ Wooldridge (2009) technique to estimate productivity. To investigate the linkages among productivity, IT, skills and key plant variables, the authors estimate specifications using system generalized method of moments (sys-GMM). Advanced estimation techniques such as Heckman two-step process, probit equations, inverse Mills ratio and panel cointegration are applied to overcome problems of nonstationarity, omitted variables, endogeneity and reverse causality.FindingsThe results indicate that the level of IT capital influences the TFP of Indian industries, so does the level of skilled workers. The outcome suggests that intermediate capital goods, location and ownership type enable the strength of IT capital and that in turn boosts productivity. The authors fail to find any impact of regional factors and contractual labor on IT capital and productivity. While medium-level gender diversity is statistically significant to influence productivity, however, no complementarities exist between gender diversity and IT capital accumulation. The results also indicate that IT demand of Indian industries is sensitive to availability of skilled workforce, fuel and electricity and access to short-term funding.Originality/valueTo the authors' knowledge, this is the first study to investigate the nexus among TFP, IT capital accumulation, skills and organizational factors using ASI unit level data. Besides this, the paper offers two more novelties. First, it uses Wooldridge (2009) technique to estimate productivity, which is used by a handful of studies in the context of India. Second, the study identifies factors that impact productivity growth, IT demand and its adoption in Indian industries and thus contributes to growth and development literature.

Bias-Compensated Diffusion Pseudolinear Kalman Filter Algorithm for Censored Bearings-Only Target Tracking

This letter proposes a novel bias-compensated diffusion pseudolinear Kalman filter algorithm for censored bearings-only target tracking. The proposed algorithm considers two biases caused by the censored bearing angle measurements and the correlation between the measurement vector and the pseudolinear noise. First, the inverse Mills ratio is used to rebuild the uncensored measurements, which can efficiently compensate the bias arising from the censored measurements. Then, we present a bias analysis for the censored diffusion pseudolinear Kalman filter to develop a bias compensation method, leading to the BC-DPLKF-C algorithm. Simulation results show the improved performance of the proposed Kalman filter compared with existing algorithms.

Reasons for unmet needs for health care: the role of social capital and social support in some western EU countries.

This paper focuses on the demand side factors that determine access to health care and analyses the issues of unmet needs for health care and the reasons thereof in western EU countries. A probit model is estimated from a sample of the whole population, accounting for the possibility of individual selection in unmet needs for health care (UN) (selection equation). Expanded probit models (including the inverse Mills ratio) are then used on the reasons for unmet needs (RUN) with social capital and social support as determinants and using the European Union Statistics on Income and Living Conditions dataset from 2006. In the RUN equations, the findings show that females, large households, people with low income and financial constraints, the unemployed and those in poor health have a higher probability of declaring unmet needs due to economic costs. Additionally, people in tertiary education, those with high income and the employed have a higher probability of not visiting a doctor when needed due to time constraints. Furthermore, the frequency of contact with friends and the ability to ask for help are correlated with a lower probability of unmet needs due to economic costs, while the frequency of contact with relatives is correlated with a lower probability of unmet needs due to time constraints and distance. However, the ability to ask for help is also correlated with a higher probability of not having medical care due to time constraints and the wait-and-see approach.

Sample Selection Models with Monotone Control Functions

The celebrated Heckman selection model yields a selection correction function (control function) proportional to the inverse Mills ratio, which is monotone. This paper studies a sample selection model which does not impose parametric distributional assumptions on the latent error terms, while maintaining the monotonicity of the control function. We show that a positive (negative) dependence condition on the latent error terms is sufficient for the monotonicity of the control function. The condition is equivalent to a restriction on the copula function of latent error terms. Utilizing the monotonicity, we propose a tuning-parameter-free semiparametric estimation method and establish root n-consistency and asymptotic normality for the estimates of finite-dimensional parameters. A new test for selectivity is also developed exploring the shape-restricted estimation. Simulations and an empirical application are conducted to illustrate the usefulness of the proposed methods.

Does financial advisor quality improve liquidity and issuer benefits in segmented markets? Evidence from the municipal bond market

PurposeUsing a unique sample of about 563,000 competitively bid municipal revenue bonds with financial advisors issued during the period 1998–2012, the purpose of this paper is to examine the role and influence of financial advisor quality in the municipal bond market.Design/methodology/approachThe authors use a sample of about 563,000 competitively bid municipal revenue bonds with financial advisors issued during the period 1998–2012. The authors estimate a selection model where the authors identify the factors leading to the selection of a high-quality financial advisor. The authors then, using the inverse mills ratio from the first regression, estimate the association of high-quality advisor (and other factors) with the cost of borrowing.FindingsThe results suggest that high-quality financial advisors provide a credible signal to market participants about issue and issuer quality. This signal translates to a greater number of bids for issues that use high-quality financial advisors, resulting in improved liquidity and lower borrowing costs for these issues. The results also show that the beneficial effects obtained by using higher quality financial advisors are prevalent across all categories of issues such as for refunding and non-refunding issues, and for both insured and non-insured issues. The benefits are also generally observed for issues of most size categories. The results also suggest that the passage of the Dodd–Frank Act requiring mandatory registration of financial advisors and enhanced scrutiny has only increased the benefits to issuers from using higher quality financial advisors.Originality/valueThis paper differs from previous research in several important ways. First, the study is, to the authors’ knowledge, the first study that explores the relationship between financial advisor quality and liquidity in the municipal sector. The authors show using higher quality financial advisors enhances liquidity for the issues by attracting a significantly large number of bids. Second, the sample is exclusively comprised of competitively bid revenue issues all of which rely on financial advisors. This enables us to examine more unambiguously the influence of financial advisor quality, without the confounding effects of issues without financial advisors. Third, time coverage (1998–2012) and size of the sample (roughly 563,000 bond issues) enables us to conduct varied sub-sample analyses with greater power since the resulting sub-sample partitions themselves are of very large size. This provides better and additional insights into the role of financial advisor quality. The more current data when compared to prior research enables us to examine the impact of financial advisor quality inter-temporally with special attention devoted to the period after passage of the Dodd–Frank Act.