Instrumental Variable Techniques Research Articles

Heterogeneous impact of crop diversification on farm net returns and risk exposure: Empirical evidence from Ghana

AbstractIncreasing frequency of extreme weather events threatens the livelihoods of low‐income farm households due to the heavy dependence on rain‐fed agriculture coupled with the under‐developed formal markets for risk management products. Thus, crop diversification is one of the widely used ex ante adaptation strategies to hedge against weather risk exposure. In this study, we use survey data from the northern Savanna zone of Ghana merged with historical weather data to shed light on the heterogeneous impact of crop diversification on farm net returns and risk exposure. We employ the dose response function and instrumental variable techniques to address potential endogeneity concerns. Overall, our findings show that crop diversification is a welfare‐enhancing strategy that significantly increases farm net returns, lowers the probability of crop failure, and thus decreases downside risk exposure. Notably, our dose‐response function analysis demonstrates that the positive benefits of crop diversification are particularly pronounced at lower intensities, reaching an optimal threshold. Beyond this point, the incremental advantages tend to diminish, suggesting the importance of carefully considering the optimal level of diversification for maximum benefits. The results further underscore the significant impact of both access to agricultural extension services and fertilizer usage on the adoption of crop diversification.

Determinants of Road Traffic Crash Fatalities: A Case of Road Accidents in India, 2004–2018

The purpose of this study is to determine the factors that influence deaths in road accidents in India. The study uses panel econometric methodologies such as the fixed effects model, random effects model, and Hausman–Taylor instrumental variable technique to achieve this goal. Unobserved heterogeneity between states/union territories (UTs) and time is accounted for by time-fixed and state-fixed effects. Based on the panel data set from Indian states/UTs for the period 2004–2018, the study confirms previous results that motorisation, population, urbanisation and income level are all potential contributors to road accidents and fatalities. It also shows that spending on health care and law enforcement appears to help the Indian states minimise mortality in road traffic accidents. On the one hand, spending on health care facilities can provide health-related assistance to persons who have been involved in traffic accidents; on the other hand, spending on police increases the enforcement of rules, resulting in a reduction in traffic accidents. Thus, to lessen the economic and financial cost of road accidents in the country, the government should focus on boosting both per capita health expenditure and per capita police expenditure. JEL Codes: C23, C26, H51, I18, L92, O18, R41, R42

Enhancing rational approximation of wideband resonant MIMO systems with frequency-domain data

Vector Fitting (VF) is a successful methodology for both time and frequency domain estimation of dynamic systems. These algorithms have gained popularity as a system identification tool due to their ability to provide a practical procedure for accurately approximating the measured frequency response behavior of complex and highly resonant dynamic systems using rational models. Instrumental Variable (IV) techniques can also be added to the VF algorithm to enhance the optimality of the solutions in the presence of measurement noise. In this context, this paper presents a multiple-input multiple-output (MIMO) generalization of instrumental variable (IV-)VF. The proposed algorithm can be applied to accurately estimating models formed by either continuous- or discrete-time rational basis functions (RBFs). We show that such a generalization preserves the main implementation features observed in Standard VF, but with improved optimality property for its solutions. Additionally, in order to alleviate convergence problems that may arise from the fixed high-frequency normalization, we also present in this paper how to incorporate in the proposed IV-VF method the relaxed formulation found in standard VF for both the continuous and discrete-time cases. The resulting MIMO IV-VF algorithm can be easily understood by VF users, and its applicability is discussed by using an estimation case study with two power system pieces of equipment (an 88 kV Transformer and a 550 kV Instrument Transformer) for which actual frequency domain measurements were collected in the field. It is shown that the proposed algorithm significantly improves the modeling accuracy when compared to standard VF algorithms.

Consistent two-stage estimation in heterogeneous network autoregressive model

Obtaining consistent estimates of network effects in heterogeneous network autoregressive model presents significant challenges. These arise from the large number of target parameters, potential endogeneity, and non-identifiability issues. To overcome these challenges, we reformulate the model into a higher-order version. Our proposed two-stage estimation procedure first reduces parameter complexity by screening out nodes with negligible network effects. Then, we employ the ordinary least squares method and the instrumental variables technique for effective post-screening estimation. We further investigate the consistency and asymptotic normality of the estimators under appropriate assumptions and explore the case of heteroscedasticity. The finite sample performance of the two-stage method is evaluated by simulation studies and an empirical analysis.

The effects of mother's schooling on next generation’s schooling: evidence from Bangladesh

PurposeThis paper aims to find the effects of mothers’ schooling on child schooling.Design/methodology/approachThis paper uses Bangladesh's Household Income and Expenditure Survey (HIES), which is a nationally representative survey. It employs the instrumental variable technique to estimate the intergenerational model.FindingsInterestingly, the results show that the intergenerational transmission of schooling from mothers is slightly higher than that of fathers in Bangladesh.Research limitations/implicationsEstimating the intergenerational model is challenging due to the endogeneity issue. The methodology used in this paper may help to find similar evidence from other countries.Practical implicationsThe findings of the study may help to design and evaluate the educational policies in Bangladesh or a country like Bangladesh. For instance, the results of this paper suggest that the female stipend program (FSP) in Bangladesh is effective for the next generation’s schooling.Originality/valueThis paper is among the first to analyze the effect of mother’s schooling on the child’s schooling, controlling the father’s education and other household characteristics. In addition, it controls for endogeneity bias due to genetic transmission.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0491

Estimating the direct rebound effect for residential electricity use in seventeen European countries: Short and long-run perspectives

The energy saved by improving the building efficiency of European households may not be as much as expected due to a rebound effect. Based on Eurostat and World Bank annual panel data covering the period 1996–2020, this article develops dynamic panel approaches, a generalized method of moments, and first-difference specifications, to investigate the direct rebound effect of residential electricity consumption in selected European countries. Instrumental variable techniques are used to tackle the reverse causality of the electricity price in a demand model. Estimates of the direct rebound effect in residential electricity use are 18% in the short-run and 43% in the long-run. Our findings reject the hypothesis of a backfire effect in residential electricity demand. They have important implications for policy makers, suggesting the need for smart policies that consider energy consumption behaviors and decision-making processes among various households.

How Does Transport‐Related Deprivation Reduce Hours of Work in Australia?1

In this study, we examine the effect of transport‐related deprivation on hours of work using 17 waves of longitudinal data from the Household, Income and Labour Dynamics in Australia. We measure transport‐related deprivation using indicators that reflect transport accessibility and affordability. The overall finding indicates that transport‐related deprivation reduces hours of work. This outcome is more pronounced for public transport than private transport, and consistent across instrumental variable techniques, an alternative fixed effect model, and heterogeneity analysis. Further analysis reveals that the hours of work‐reducing effect of transport‐related deprivation is transmitted through time spent travelling to work.

Examining the role of artificial intelligence in advancing pollution reduction strategies

AbstractThis study is based on the panel data from 2006 to 2020 to explore the relationship between artificial intelligence (AI) and pollution emission. The study demonstrates a notable and statistically significant reduction in pollution emission intensity attributable to AI. This finding is robust, holding up under various sensitivity analyses and addressing endogeneity using instrumental variable techniques. The mechanism analysis reveals that AI's role in decreasing emissions primarily arises from three factors: the promotion of technological innovation, increased investment in emission reduction technology, and the replacement of low‐skilled labor with more efficient alternatives. We also find more substantial environmental benefits in areas with stricter environmental regulations and higher initial levels of pollution. Additionally, AI is shown to facilitate a symbiotic relationship between economic growth and environmental management. This research provides both empirical evidence and theoretical insights that reinforce the essential role of AI in driving green transformations, process upgrades, and high‐quality development. It situates these advancements within the broader context of the interplay between artificial intelligence, environmental sustainability, and economic progression.

Preferential employment policies and firm performance: Evidence from Indian public sector enterprises

This article examines the impact of job reservations on the performance of public sector enterprises (PSEs) in India. Drawing on data for all central government‐owned manufacturing PSEs from 2014 to 2017 and employing instrumental variable techniques, the authors test the hypothesis that reservations benefit firm performance if implemented across all levels of the employment hierarchy. While the findings validate this hypothesis, they also indicate that the reserved categories are disproportionately represented in the lower end of the organizational hierarchy. This imbalance is primarily driven by systematic limitations in vacancy notifications and discriminatory practices within organizations.

Residential energy expenditures and the relevance of financial inclusion across location, wealth quintiles and household structures

This paper examines the relative role of financial inclusion in enhancing households’ ability to spend on energy consumption across rural and urban locations. It uses comprehensive household data from Ghana and employs the ordinary least square (OLS) as well as an instrumental variable estimation technique. Endogeneity of financial inclusion is instrumented using distance to the nearest bank. Our findings suggest that a standard deviation increase in financial inclusion contributes to an improvement in residential energy expenditure by 1.2835 standard deviations. This finding is robust to different methods for resolving endogeneity and alternative weighting schemes in the financial inclusion construct. Among the different sources of energy for lighting and cooking, financial inclusion increases expenditure on LPG and electricity more than the others. Financial inclusion increases the ability to spend more on residential energy in urban, poorest, and female-headed dual-parent households. Household net income is a key pathway through which financial inclusion affects residential energy expenditure.

Does national forest city improve residents' health? Evidence from China.

National health is essential for economic and social development. The aim of this article is to examine the relationship, heterogeneity effects and influential mechanisms between National Forest Cities and the residents' health. The article matches the China Family Panel Studies data in 2018 (CFPS2018) with the 2016-2018 National Forest Cities Construction List, resulting in a final sample of 20,041. Oprobit, Ologit, Instrumental Variable technique (2SLS) and interaction term analysis were used as the main research methods in this article. The findings indicate that: (1) The construction of National Forest Cities significantly improves the residents' health in terms of both physical and mental health, and this conclusion is still valid after a series of robustness tests. (2) On the one hand, National Forest Cities promote residents' health by reducing air pollutants such as SO2 and soot to reduce residents' health risk exposure; On the other hand, it promotes residents' health by positively guiding them to engage in healthy behaviors. (3) National Forest Cities have a greater effect on the health of urban residents, older adult and lower-income group, suggesting that National Forest Cities are a public benefit. The construction of National Forest Cities is a public welfare that promotes residents' health, and it is an important revelation for accelerating the realization of the Healthy China Strategy. The article provides new empirical evidence for understanding the welfare effects of forest cities and offers new practical paths for improving residents' health.

From subsistence to market-oriented farming: The role of groundwater irrigation in smallholder agriculture in eastern India

Empowering smallholder farmers in low and middle-income countries (LMICs) and improving their livelihood is a critical goal for poverty reduction. To achieve this, agricultural commercialization can play an important role. However, a prerequisite to achieving agricultural commercialization is access and control of stable irrigation. This study revisits empirically the relationship between groundwater irrigation and crop commercialization. It also analyses the underlying mechanisms of how groundwater affects crop commercialization through on-farm production diversity. Studying the effects of groundwater irrigation on crop commercialization is essential for comprehending the trade-off between agricultural benefits and the environmental costs of groundwater irrigation. Geospatial and remote sensing information, combined with primary household data from small-scale farmers in eastern India, are employed in conjunction with an instrumental variable technique and a 3SLS simultaneous equation model for the analysis. The results suggest that small-scale farmers in eastern India experience enhanced crop commercialization when they have access to groundwater irrigation. Furthermore, the study suggests that the utilization of groundwater irrigation indirectly promotes crop commercialization by incentivizing farmers to diversify their production system.

Crowding-out effect of tobacco consumption in Indonesia.

Tobacco consumption is pervasive in Indonesia, with 6 out of 10 households in the country consuming tobacco. Smoking households, on average, divert a significant share (10.7%) of their monthly budget on tobacco products, which is higher than spending on staples, meat or vegetables. Nevertheless, evidence of the causal link between tobacco expenditure and spending on other commodities in Indonesia is limited. This study aims to estimate the crowding-out effects of tobacco spending on the expenditure of other goods and services in Indonesia. This research estimates the conditional Engel curve with three-stage least square regression, where the instrumental variable technique is applied to address the simultaneity of tobacco and total non-tobacco spending. The study employs a large-scale household budget survey from the Indonesian socioeconomic survey (Susenas) from 2017 to 2019, comprising over 900 000 households. Tobacco spending crowds out the share of a household's budget allocated for food, such as spending on staples, meat, dairy, vegetables and fruits. Moreover, tobacco spending also reduces the share of expenditure spent on non-food commodities, such as clothing, housing, utilities, durable and non-durable goods, education, healthcare and entertainment, although its effect is not as large as the crowding out on food. The analysis shows that the crowding-out effects of tobacco are observed across low-income, middle-income and high-income households. In addition, the simulation suggests that reducing tobacco expenditure will increase household spending on essential needs.

The impact of diet quality on cognitive ability of Chinese older adults: evidence from the China Health and Nutrition Survey (CHNS)

BackgroundNumerous studies have demonstrated a positive correlation between diet quality and cognitive performance, indicating that improving diet quality may be beneficial in preventing cognitive decline in older adults. However, few study has investigated the causal relationship between diet quality and cognitive performance. The purpose of this study is to evaluate the causal effects of diet quality on cognitive performance in Chinese adults aged 55 years and older. Particularly, we utilize the Chinese Diet Quality Index (CHEI), a dietary assessment tool tailored for Chinese populations, as a proxy for older adults’ diet quality.MethodsData were obtained from the China Health and Nutrition Survey (CHNS) (N=2337\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N = 2337$$\\end{document}, ≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge$$\\end{document}55 years old) conducted in 2004 and 2006. Cognitive function was tested by a subset of items from the Telephone Interview for Cognitive Status-Modified (TICS-m). Data on dietary intake was retrieved from three consecutive 24 hour recalls by participants and its quality was assessed by the 17-items Chinese Healthy Eating Index (CHEI). An Instrumental Variable technique was used to deal with the potential endogeneity of dietary quality. The instrumental variable used in our study is the community mean of CHEI.ResultsAfter adjusting for socio-demographic factors (age, gender, education, per capita household income), lifestyle habits (smoking, alcohol consumption, physical activity, BMI), and chronic diseases (hypertension, diabetes), our findings revealed that improving diet quality had a significant positive effect on cognitive performance (P=0.020\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P = 0.020$$\\end{document}), particularly in females aged 55-65 years (P=0.003\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P = 0.003$$\\end{document}) and females with primary education and below (P<0.001\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P < 0.001$$\\end{document}).ConclusionOur study suggests that improving diet quality and adhering to the Dietary Guidelines for Chinese may enhance cognitive performance in Chinese adults aged 55 years and older.

Nexus between information and communication technologies and life expectancies of low-income countries: Does technological advancement increase their life span?

Access to state-of-the-art infrastructure is inevitable for a higher standard of living for the people of any country. At least, this has been the case for developed countries. This study investigates the link between information and communication technologies (ICT) and life expectancy at birth (LEB) among low-income countries. We use panel data of low-income countries from 2000 to 2017 from the comprehensive World Bank dataset. Our analysis strategy includes employing Driskol and Kraay methodology and feasible generalized least squares to tackle cross-sectional dependence. Furthermore, we also employ the instrumental variable technique to deal with the endogeneity problem. We found that a rise in mobile internet use and Mobile Cellular Subscriptions led to improved LEB among low-income countries. On the contrary, the rise in fixed telephone subscriptions had a negative empirical effect on reducing LEB—however, the magnitude of the effect ranged between 0% and 4%.

CEO power and stock price crash risk in India: the moderating effect of insider trades

PurposeThis study aims to explore the relationship between chief executive officer (CEO) power and stock price crash risk in India. Furthermore, it seeks to analyse how insider trades may moderate the impact of CEO power on stock price crash risk.Design/methodology/approachA study of 236 companies from the S&amp;P BSE 500 Index (2014–2023) have been analysed through pooled ordinary least square (OLS) regression in the baseline analysis. To enhance the results' reliability, robustness checks include alternative methodologies, such as panel data regression with fixed-effects, binary logistic regression and Bayesian regression. Additional control variables and alternative crash risk measure have also been utilised. To address potential endogeneity, instrumental variable techniques such as two-stage least squares (IV-2SLS) and difference-in-difference (DiD) methodologies are utilised.FindingsStakeholder theory is supported by results revealing that CEO power proxies like CEO duality, status and directorship reduce one-year ahead stock price crash risk and vice versa. Insider trades are found to moderate the link between select dimensions of CEO power and stock price crash risk. These findings persist after addressing potential endogeneity concerns, and the results remain consistent across alternative methodologies and variable inclusions.Originality/valueThis study significantly advances research on stock price crash risk, especially in emerging economies like India. The implications of these findings are crucial for investors aiming to mitigate crash risk, for corporations seeking enhanced governance measures and for policymakers considering the economic and welfare consequences associated with this phenomenon.

The Ends of 27 Big Depressions

How did countries recover from the Great Depression? In this paper, we explore the argument that leaving the gold standard helped by boosting inflationary expectations, lowering real interest rates, and stimulating interest-sensitive expenditures. We do so for a sample of 27 countries, using modern nowcasting methods and a new data-set containing more than 230,000 monthly and quarterly observations for over 1,500 variables. In those cases where the departure from gold happened on well-defined dates, inflationary expectations clearly rose in the wake of departure. Instrumental variable, difference-in-difference, and synthetic matching techniques suggest that the relationship is causal. (JEL E31, E32, E42, E43, F30, N10, N20)

Mineral resource sustainability in the face of the resource exploitation and green recovery: Challenges and solutions

China's mining sector faces a pressing need to align profitability with eco-friendly resource extraction for sustainable development. Our study delves into the pivotal role of Renewable Energy Technology Innovation (RETI) in enhancing resource efficiency within this context. Analyzing data spanning 40 Chinese regions from 2000 to 2021, our research uncovers notable regional variations in RETI's impact on mineral resource sustainability. Rigorous validation measures, including addressing outliers and utilizing instrumental variable techniques, ensure the robustness of our findings. Specifically, RETI emerges as a catalyst for improving green mining resource efficiency in the Midwest and West regions but exhibits no parallel effect in the East. Crucially, the influence of RETI is intricately tied to changes in economic and human capital, offering valuable insights to expedite its adoption and optimize mineral asset sustainability in China's mining sector. This research contributes essential perspectives to propel the sector toward environmentally conscious practices and underscores the significance of adapting to cleaner energy sources for long-term viability.

Estimation in Semi-Varying Coefficient Heteroscedastic Instrumental Variable Models with Missing Responses

This paper studies the estimation problem for semi-varying coefficient heteroscedastic instrumental variable models with missing responses. First, we propose the adjusted estimators for unknown parameters and smooth functional coefficients utilizing the ordinary profile least square method and instrumental variable adjustment technique with complete data. Second, we present an adjusted estimator of the stochastic error variance by employing the Nadaraya–Watson kernel estimation technique. Third, we apply the inverse probability-weighted method and instrumental variable adjustment technique to construct the adaptive-weighted adjusted estimators for unknown parameters and smooth functional coefficients. The asymptotic properties of our proposed estimators are established under some regularity conditions. Finally, numerous simulation studies and a real data analysis are conducted to examine the finite sample performance of the proposed estimators.

Migration, Remittance and Poverty Dynamics in Rural India: Evidence from Longitudinal Survey

As rural poverty continues to pose fundamental challenges in the development process, this study aims to examine the role of remittance in influencing poverty dynamics among rural households. For this, we employed instrumental variable technique and utilized longitudinal data of India Human Development Survey. After correcting for endogeneity bias results obtained from our econometric analysis reinforce the urgent need to focus on poverty transition in rural households and highlight the positive and significant role of the amount and frequency of remittances in alleviating poverty. Additionally, access to credit, government subsidies, and educational attainment substantially improves rural households’ economic condition and helps them to escape poverty. Education can be a magical tool to deal with poverty, so there is need to restore the quality of education in rural areas. Thus, in order to achieve poverty elimination goal, there is a need to integrate migration and poverty while considering policy measures. Given the importance of amount and frequency of remittances in poor households, it is imperative from policy perspective to focus upon the channels of smoothing the flow of external finance and make it more sustainable.