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Poverty remains a substantial threat in rural areas of many developing countries, and solving this problem requires an in-depth understanding of the income generating capacity that determines poverty. This paper examines the impact of agricultural commercialisation on the capability of rural households to accumulate and productively use assets and reduce structural and multidimensional poverty. A longitudinal dataset of around 2000 households with a total of 9781 observations from five rural surveys undertaken in the period 2008–2017 in Vietnam is used. Results from a fixed effects regression with an instrumental variable and a control function approach show that agricultural commercialisation has a positive effect on the accumulation of assets and reduces multidimensional and structural poverty over time. However, the effect is not homogeneous and is larger for households that are not mainly engaged in rice commercialisation. This suggests that commercialisation can be a path out of poverty, especially if policy makers move towards utilising other crops instead of rice.

Members of Congress represent geographically demarcated districts embedded in subnational policy environments. Drawing on policy feedback literature and literature on congressional representation, I argue that, because of this institutional configuration, subnational policy adoption can affect national representation. More specifically, policy reforms in the states they represent can increase pressures members face from organized groups and individuals in their constituencies to promote aligned federal policies. Empirically, I examine the effects of state marijuana legalization. The inferential design leverages differences across the states in statewide citizen initiative institutions, which provides exogenous variation in legalization. Instrumental variables analysis indicates legalization influenced pro-marijuana bill sponsorship and roll calls in the 116th Congress. The evidence points to growing influence of industry in legalizing states—including the ability to mobilize employees and customers—as the key mechanism, thus underscoring the importance of a political economy perspective for studying interdependencies in American federalism.

Workplace flexibility offers a wide range of opportunities but also carries risks within the context of collaborative tasks. While increasing the number of collaborators can reduce fatigue and therefore enhance performance, it also increases coordination costs. Our study investigates this trade-off in a complex team task with high effort costs in a natural setting. We use the instrumental variables method combined with an extensive sensitivity analysis to identify the causal effect of in-game substitutions on performance in professional basketball. Our findings suggest that increasing the number of collaborators, on balance negatively affects team performance. However, we also provide evidence that the most successful teams are able to optimally trade off both effects.

Mendelian randomization (MR) is an application of instrumental variable (IV) methods to observational data in which the IV is a genetic variant. MR methods applicable to the general exponential family of distributions are currently not well characterized. We adapt a general linear model framework to the IV setting and propose a general MR method applicable to any full-rank distribution from the exponential family. Empirical bias and coverage are estimated via simulations. The proposed method is compared to several existing MR methods. Real data analyses are performed using data from the REGARDS study to estimate the potential causal effect of smoking frequency on stroke risk in African Americans. In simulations with binary variates and very weak instruments the proposed method had the lowest median [Q1 , Q3 ] bias (0.10 [-3.68 to 3.62]); compared with 2SPS (0.27 [-3.74 to 4.26]) and the Wald method (-0.69 [-1.72 to 0.35]). Low bias was observed throughout other simulation scenarios; as well as more than 90% coverage for the proposed method. In simulations with count variates, the proposed method performed comparably to 2SPS; the Wald method maintained the most consistent low bias; and 2SRI was biased towards the null. Real data analyses find no evidence for a causal effect of smoking frequency on stroke risk. The proposed MR method has low bias and acceptable coverage across a wide range of distributional scenarios and instrument strengths; and provides a more parsimonious framework for asymptotic hypothesis testing compared to existing two-stage procedures.

Research on immigration and innovation points out that immigrants can directly enhance the destination's innovation capacity and generate innovation effects by promoting cultural diversity in the host country. This paper combines province-level data of the number of international students with 284 cities panel data from 2001 to 2015 and finds that international student inflow has a significant positive effect on the city innovation index. Due to the innovation effect of cultural diversity has certain transaction costs, international students' influence on the city's innovation ability is non-linear; choosing the share of undergraduate students in the total population as the threshold variable and finding the threshold value is 4.3716%. Furthermore, using the dialect diversity index as a proxy variable for cultural diversity, I find that reducing the negative impact of dialect diversity on city innovation is vital for international students to promote city innovation. Considering the possible endogenous problems and missing variables, I apply a shift-share instrumental variable approach and take a series of robustness checks; the conclusions are still robust.

Background and AimsInitial use of drugs such as tobacco and alcohol may lead to subsequent more problematic drug use—the ‘gateway’ hypothesis. However, observed associations may be due to a shared underlying risk factor, such as trait impulsivity. We used bidirectional Mendelian randomization (MR) to test the gateway hypothesis.DesignOur main method was inverse-variance weighted (IVW) MR, with other methods included as sensitivity analyses (where consistent results across methods would raise confidence in our primary results). MR is a genetic instrumental variable approach used to support stronger causal inference in observational studies.Setting and participantsGenome-wide association summary data among European ancestry individuals for smoking initiation, alcoholic drinks per week, cannabis use and dependence, cocaine and opioid dependence (n = 1749–1 232 091).MeasurementsGenetic variants for exposure.FindingsWe found evidence of causal effects from smoking initiation to increased drinks per week [(IVW): β = 0.06; 95% confidence interval (CI) = 0.03–0.09; P = 9.44 × 10−06], cannabis use [IVW: odds ratio (OR) = 1.34; 95% CI = 1.24–1.44; P = 1.95 × 10−14] and cannabis dependence (IVW: OR = 1.68; 95% CI = 1.12–2.51; P = 0.01). We also found evidence of an effect of cannabis use on the increased likelihood of smoking initiation (IVW: OR = 1.39; 95% CI = 1.08–1.80; P = 0.01). We did not find evidence of an effect of drinks per week on other substance use outcomes, except weak evidence of an effect on cannabis use (IVW: OR = 0.55; 95% CI = 0.16–1.93; P-value = 0.35). We found weak evidence of an effect of opioid dependence on increased drinks per week (IVW: β = 0.002; 95% CI = 0.0005–0.003; P = 8.61 × 10−03).ConclusionsBidirectional Mendelian randomization testing of the gateway hypothesis reveals that smoking initiation may lead to increased alcohol consumption, cannabis use and cannabis dependence. Cannabis use may also lead to smoking initiation and opioid dependence to alcohol consumption. However, given that tobacco and alcohol use typically begin before other drug use, these results may reflect a shared risk factor or a bidirectional effect for cannabis use and opioid dependence.

This article examines the impact of domestic remittances on the labour supply of men and women in recipient households in rural India. Applying the instrumental variable approach to data from the National Sample Survey, estimates indicate that remittances have a negative effect on the labour force participation of left‐behind household members. They do not seem to affect participation in regular salaried work but cause a decline in participation in casual wage work and unpaid family work, and an increase in self‐employment, especially among female household members. Additionally, the receipt of remittances significantly increases women's participation in household duties outside the labour market.

Apprenticeship may provide an important opportunity to improve human capital and future earnings of young people, especially those with low levels of education. Based on new administrative data, we provide the first empirical evidence of the effect on wages and employability of the mobility across firms and economic sectors of apprentices after graduation in Italy. We use an instrumental variable approach to account for endogenous selection that is based on observed and unobserved characteristics when estimating the causal effects of mobility. Our main finding is that job switchers outside the economic sector of the training firm faced a considerable gap in wages and weeks worked in comparison to stayers in the training firm, indicating a loss of firm-specific human capital. In addition, the new apprenticeship introduced by the Biagi reform, which lessened the stringency of the norms on the training content delivered by firms, resulted in further reductions of the transferability of skills for trainees relative to the previous regime. Overall, the apprenticeship contract in Italy generated earning gaps according to the workers’ mobility after graduation, thus increasing inequality among similar employees.

Strong empirical evidence points towards a significantly higher prevalence of opioid consumption among people receiving disability benefits (DB) than in the general population of the United States. However, no previous research established a causal relationship between the decision to award DB to applicants and their subsequent opioid use. We aim to contribute towards filling this gap. There are channels through which awarding DB may both increase and depress opioid consumption, and thus, ex ante, the sign of a potential causal relationship is ambiguous. To correct for the treatment endogeneity, since an individual's age at the time of the decision on an application impacts discontinuously at certain age cutoffs the award decision, we employ a fuzzy Regression Discontinuity model with three age cutoffs used for identification. We find that awarding DB increases the likelihood of using opioids by about 27-30 percentage points. This suggests that the positive association between DB receipt and opioid consumption is likely to be causal.

We study the effects of foreign exchange hedging on corporate innovation. According to the information asymmetry hypothesis, corporate hedging reduces firms' information asymmetry, alleviates managers' career concerns, and helps investors better monitor managers, which enhances innovation. According to the market pressure hypothesis, hedging imposes short‐term earnings pressure on managers as a result of mark‐to‐market hedge accounting, discouraging innovation. Using 32,194 observations of 5847 nonfinancial firms from 1998 to 2006, we document results that support the information asymmetry hypothesis. Hedged firms invest more heavily in innovative projects, generate more patents, and have more patent citations. To address endogeneity concerns, we employ both difference‐in‐differences and instrumental variable regressions and explicitly test for reverse causality.

In this paper, we develop a two-stage approach to estimate the treatment effects of dummy endogenous variables using high-dimensional instrumental variables (IVs). In the first stage, instead of using a conventional linear reduced-form regression to approximate the optimal instrument, we propose a penalized logistic reduced-form model to accommodate both the binary nature of the endogenous treatment variable and the high dimensionality of the instrumental variables. In the second stage, we replace the original treatment variable with its estimated propensity score and run a least-squares regression to obtain a penalized Logistic-regression Instrumental Variables Estimator (LIVE). We show theoretically that the proposed LIVE is root-n consistent with the true treatment effect and asymptotically normal. Monte Carlo simulations demonstrate that the LIVE is more efficient than existing IV estimators for endogenous treatment effects. In applications, we use the LIVE to investigate whether the Olympic Games facilitate the host nation's economic growth and whether home visits from teachers enhance students' academic performance. In addition, the R functions for the proposed algorithms have been developed in an R package, naivereg.

Public long-term care (LTC) systems provide services to support people experiencing difficulties with their activities of daily living. This study investigates the marginal effect of changes in public LTC expenditure on care-related quality of life (CRQoL) of existing service users in England. The public LTC program for people aged 18 or older in England is called Adult Social Care (ASC) and it is provided and managed by local authorities. We collect data on the outcomes and characteristics of public ASC users, on public ASC expenditure, and on the characteristics of local authorities across England in 2017/18. We employ an instrumental variable approach using conditionally exogenous elements of the public funding system to estimate the effect of public ASC expenditure on user CRQoL. Our findings show that by increasing public ASC expenditure by £1000 per user, on average, local authorities increase user CRQoL by 0.0030. These results suggest that public ASC is effective in increasing users' quality of life but only to a relatively small extent. When combined with the other potential effects of LTC expenditure (e.g., on informal carers, mortality), this study can inform policy makers in the United Kingdom and internationally about whether social care provides good value for money.

The aim of mediation analysis is to identify and evaluate the mechanisms through which a treatment affects an outcome. The goal is to disentangle the total treatment effect into two components: the indirect effect that operates through one or more intermediate variables, called mediators, and the direct effect that captures the other mechanisms. This paper reviews the methodological advancements in causal mediation literature in economics, in particular focusing on quasi-experimental designs. It defines the parameters of interest under the counterfactual approach, the assumptions and the identification strategies, presenting the Instrumental Variables (IV), Difference-in-Differences (DID) and the Synthetic Control (SC) methods.

While trademarks are mentioned in many firms’ IPO prospectuses, their influences on the IPO valuation process are underexplored. This paper studies the relationship between a firm’s pre-IPO trademarks and its IPO underpricing. Using 4,457 US IPOs during the period 1980-2018 we find that firms with a larger number of trademarks prior to the IPO date experience significantly less IPO underpricing. We employ a quasi-natural experiment brought about by the 1996 Federal Trademark Dilution Act and an instrumental variable approach to establish causality. Our findings suggest that trademarks help reduce information asymmetry among various IPO participants, leading to less underpriced IPOs.

We use the presence of a Wikipedia article for initial public offering (IPO) firms to test theories of information asymmetry and investor awareness. While we find limited support for the former, our results provide strong support for theories of investor awareness. Specifically, IPO firms with a Wikipedia article exhibit significantly higher underpricing and offer price revisions than do IPO firms without a Wikipedia article. Investor awareness has positive long-term effects, including greater analyst following and institutional ownership for up to three years after the offering. The effect is robust to firm-specific Google search volume, news coverage, retail trading intensity, social media activity, propensity score matching, and an instrumental variable approach.

This article analyzes how urban proximity introduces spatial heterogeneity in farm productivity within the high‐value dairy sector in one of the poorest countries in Africa, Ethiopia. We look at how urban proximity—measured as travel time—affects the decisions and productivity of milk farmers located in rural production zones serving fresh milk to the capital Addis Ababa. Using an instrumental variable approach, we find that with each additional hour of travel time, farmers’ milk productivity per cow is reduced, on average, by almost 1 L per day or by 26%. When trying to disentangle the underlying mechanisms (and controlling for transaction costs), we find that farmers’ inclusion in “modern” value chains and their access to commercial milk buyers and milk processing companies drive the urban proximity effect. As only a limited number of farmers have access to such value chains in developing countries, measures to make dairy value chains more inclusive to remote—often poorer—farmers can, therefore, have important benefits for them, for the performance of the dairy sector in Ethiopia, and for the process of agricultural transformation as a whole.

Do firms in China share rents with their workers? We address this question by examining firm-level panel data covering virtually all manufacturing firms over the period 2000-2007, representing an average of 200,000 firms and 54 million workers per year. We find robust evidence of rent sharing (RS): workers that would move from low- to high-profit firms would see their wages increase by about 45%. The results are based on multiple instrumental variables, including firm-specific international trade shocks. We also present a number of complementary findings that allow us to understand better the nature of RS in the country: RS is weaker in firms with more women and less educated workers; RS involves an element of risk sharing, as wages also decrease when profits fall; RS is lower in regions with more latent competition from rural workers; higher minimum wages tend to reduce RS; and, while employer labour market power reduces wages, it increases RS. Overall, despite its importance, RS in China is smaller and more symmetric than in developed economies, which reflects the weaker bargaining power of its workers and the different scope of its labour market institutions.

Background Mendelian randomization (MR) applies instrumental variable (IV) methods to observational data using a genetic variant as an IV. Several Monte-Carlo studies investigate the performance of MR methods with binary outcomes, but few consider them in conjunction with binary risk factors. Objective To develop a novel MR estimator for scenarios with a binary risk factor and outcome; and compare to existing MR estimators via simulations and real data analysis. Methods A bivariate Bernoulli distribution is adapted to the IV setting. Empirical bias and asymptotic coverage probabilities are estimated via simulations. The proposed method is compared to the Wald method, two-stage predictor substitution (2SPS), two-stage residual inclusion (2SRI), and the generalized method of moments (GMM). An analysis is performed using existing data from the CLEAR study to estimate the potential causal effect of smoking on rheumatoid arthritis risk in African Americans. Results Bias was low for the proposed method and comparable to 2SPS. The Wald method was often biased towards the null. Coverage was adequate for the proposed method, 2SPS, and 2SRI. Coverage for the Wald and GMM methods was poor in several scenarios. The causal effect of ever smoking on rheumatoid arthritis risk was not statistically significant using a variety of genetic instruments. Conclusions Simulations suggest the proposed MR method is sound with binary risk factors and outcomes, and comparable to 2SPS and 2SRI in terms of bias. The proposed method also provides more natural framework for hypothesis testing compared to 2SPS or 2SRI, which require ad-hoc variance adjustments.

Several studies have estimated effects of body mass index (BMI) on labour market outcomes, and these studies have mixed findings. A significant challenge has been to adequately control for omitted variables, selection, reverse causality, and measurement error. We examine the impact of BMI on income using genetic variants as instrumental variables for BMI. Individual-level pre-tax income from tax records was merged with health survey data containing measured height and weight, and data on genetic variants. The analyses were stratified by sex and a variety of methods were used to explore the sensitivity and validity of the instrumental variable (IV) strategy. For females we found that BMI had a negative effect on the logarithm of income. The effect estimated from the IV models (-0.02) was larger than the effect estimated from naïve ordinary least squares regressions (-0.01). For males, the coefficients for the effect of BMI on income were imprecise, and both positive and negative coefficients were estimated depending on the estimation method. Our results suggest that females are susceptible to reduced income levels following increased BMI.

Our paper is the first to examine the impact of government‐firm collusion on firm tax avoidance in China by applying an instrumental variable approach. We take political turnover of local leaders as an external shock to the existing collusion and investigate firms' tax avoidance activities during local leadership transition. By using data on political turnover of prefectural leaders and listed firms from 2007 to 2014, we find that political turnover leads to the instability of existing collusion, and consequently a decrease in firm tax avoidance. This provides evidence of the pre‐existing collusion between government and firms. We then rule out the possibility that such change is driven by the effect of political uncertainty or tax competition by considering the heterogeneous effect of firms and cities. Finally, we show that firms' political connections, captured by political ties and ownership of firms, stabilize the existing collusion and help firms maintain their advantage while facing external political shocks.

Research abstract We examine whether and how foreign environmental standards influence global sourcing decisions. Taking a question‐driven approach, we find a negative association between the stringency of a country's environmental standards and its share in US imports for 82 manufacturing industries across 77 countries between 2006 and 2016. This pollution haven effect holds not only for sourcing from owned foreign operations (offshore integration), but also for sourcing from unrelated third parties abroad (offshore outsourcing), and is stronger in industries with high toxic emissions and low technological intensity. These results are robust across alternative measures of environmental stringency and to using the Kyoto Agreement as an instrumental variable. These findings shed new light on how firms use global sourcing, and especially offshore outsourcing, to arbitrage across institutional environments. Managerial summary Prior work has shown that multinational firms prefer to locate their plants in countries with weak environmental standards: the so‐called Pollution Haven Effect. We extend this research to show that firms not only source from countries with weak environmental standards from their own plants, but also from third‐party foreign suppliers. Using Census data on US manufacturing imports from 77 countries between 2006 and 2016 we show that when the stringency of environmental standards in a country decreased, sourcing from that country increased, and that this effect was just as strong for sourcing from third parties as from owned operations. Our study thus suggests that previous work may have substantially underestimated the pollution haven effect, by focusing on owned global sourcing rather than all global sourcing.

This study examines the role of high‐yielding maize varieties as one of the key drivers of smallholder farmers’ market participation in a highly subsistence rural economy. The analysis is based on the End‐of‐Program Survey data collected by the Seeds of Life program in 2016 covering 700 households in rural Timor‐Leste. The results reveal significant positive impacts of technology adoption on farmers’ market participation. Households where women are relatively more active in agriculture than men are more likely to engage in agricultural commerce. The results also show a positive impact of technology adoption on maize productivity. These findings present the first empirical evidence of the causal link between technology adoption and market participation choices.

Studies on the relationship between housing prices and firm behaviours have focused on the relationship between housing prices and firm financing and investment decisions. However, housing prices may affect other firm decisions. This study investigates the impact of housing prices on manufacturing firm productivity in China. To identify the causal effect, we use a national land regulation policy and city‐level developable land area as exogenous sources of variation in housing prices. Using an instrumental variable approach to regression analysis and firm‐level data, we find that a 10% increase in housing prices leads to a 2.1% reduction in manufacturing firms' total factor productivity (TFP). An important transmission channel is the inflow of bank credit to the real estate market caused by rising housing prices, thus crowding out loans to manufacturing firms. Due to China's distinctive dual‐track land market, rising housing prices do not translate into an increase in the price of industrial land; therefore, collateral values for manufacturing firms do not increase. We further find that the negative effect of housing prices on TFP is more pronounced for firms with greater external financial dependence or greater financial constraints.

Exploiting a novel measure of firm-level political risk based on earnings conference calls, we explore the effect of political exposure on corporate social responsibility (CSR). We show that firms more exposed to political risk invest significantly more in CSR activities. This finding is consistent with the risk-mitigation hypothesis, which posits that CSR produces moral capital that safeguards the firm in case of a negative event. Hence, firms exposed to more political risk engage in more CSR activities to take advantage of its insurance-like effect. An increase in political exposure by one standard deviation raises CSR engagement by 27.95%.

The effect on economic outcomes of ethnic diversity remains debatable. Some view ethnic diversity as a deterrent of development, whereas others consider it a source of innovation and productivity, which can be translated into a higher level of development. This study aims to shed further light on the issue. Applying instrumental variables estimation to district‐level data, we find that ethnic diversity has a significant positive association with nighttime light intensity, which is used as a proxy for level of economic activity. The finding is robust to alternative specifications. Our finding suggests that centuries of interethnic contacts and coexistence may have helped ethnically diverse communities to gain experimental knowledge of the diverse beliefs and social practices and transition it into better economic outcomes.

This study investigates the linkage between trade credit demand and corporate innovation. The estimations are robust to a series of covariates, fixed‐effect, instrumental variable modeling, and the difference‐in‐difference approach. Our findings reveal that the nexus between enterprise innovation and trade credit demand is positive and statistically significant. The said attachment is more visible in private, financially constrained, small, and high‐tech enterprises. The study also found that innovative firms relied heavily on trade‐credit financing after the financial crisis of 2008. Managers should carefully design trade‐credit agreements because operating suppliers have an important role in the enterprises' radical growth activities.

The paper investigates whether firms have better access to bank credit in territories characterized by a larger degree of urbanization. It uses Italian bank‐firm data drawn from the Credit Register to devise an indicator of easiness of access to credit. The paper proposes an instrumental variable strategy that exploits as instruments past population density and urbanization driven by political economy considerations. The results show that urbanization positively affects access to credit for construction firms, whose collateral greatly benefits from thicker real estate markets. No impact is found for service and manufacturing firms.

This paper studies the effect of export expansion on the US labour market over the last two decades. Exploiting foreign emerging markets’ unilateral liberalisation, this paper provides new empirical evidence for the importance of export expansion to the US labour market at the industry level. Using a novel instrumental variable strategy, the result confirms that US exports played a critical role in supporting manufacturing employment. Reduced‐form estimates imply that US exports to different markets created more than 1.6 million manufacturing jobs between 1991 and 2007, which is comparable to the estimated job losses attributed to the import competition from China. Meanwhile, there is substantial heterogeneity in this positive employment effect across export destinations and industries. Industries not only respond differently to various export shocks, but could also experience differential employment growth facing the same export shock. I find that the job creation effect is larger for industries with a higher initial share of workers who are older, less‐educated or non‐white, and performing routine‐based tasks. In addition, the effect is more pronounced for industries that had higher labour market concentration.

In this paper, we examine the effect of export expansion on the health of children under the age of 6 years in China. Using the CHNS survey, we exploit trade exposure variation among regions after China's entry into the WTO to construct a difference‐in‐differences and instrumental variable identification. We show that 1% increase in export expansion over GDP share exacerbates child' illness rates by 0.6%, and the effect is more pronounced for less educated parents. The increasing workloads and having less time to look after the child account for the increasing illness rates, especially for mothers.

In this paper we explore the relationship between international trade openness and two major political distortions, political polarization and political instability. We consider both the extensive and intensive margins of trade as measured by the number of trade partners and trade volume, respectively. As political distortions and trade characteristics of the country are endogenously related, we instrument political instability by the age difference between the youngest and the oldest effective political leaders of a country and the average neighbors’ neighbors political instability. We find that political instability reduces trade openness both at the extensive and intensive margin while political polarization negatively affects the extensive margin of trade. We propose a simple model that provides intuition on our findings.

The study examines financial and transaction characteristics that influence mergers and acquisitions (M&A) in U.S. agribusinesses. During the M&A private phase, we model the likelihood of firms becoming bidders or targets as a function of firms' past financial performance. During the M&A public phase, the likelihood of bidders becoming acquirers is modeled as a function of firms' past financial performance and M&A transaction characteristics. The results for the subset of bidders in the M&A private phase suggest that the likelihood of a firm becoming a bidder is positively correlated with the bidder's firm size 1 year before the M&A announcement. In contrast, the likelihood of a firm becoming a bidder is negatively associated with bidder's leverage, cash level, and very low market valuations. For the subset of targeted firms, the likelihood of firms being targeted is positively associated with the firm's leverage and negatively related with its profitability. Our results for the M&A public phase model show that firm experience in the M&A market is positively associated with the likelihood of acquisition completion. In addition, relative to nonhorizontal transactions, horizontal mergers tend to be more difficult to complete. [EconLit Citations: G34, M2].

This study examines how managers’ use of expectation management is affected by their labor market mobility, which we measure by the enforceability of non‐compete provisions in their employment contracts. Exploiting quasi‐natural experiments, our difference‐in‐differences analyses provide new causal insights to the growing literature on how managers’ career concerns affect their disclosure choices. Consistent with a less mobile labor market imposing more pressure on managers to achieve earnings expectations, we predict and find that managers in U.S. states that tightened enforcement of non‐compete provisions are more likely to manage analyst expectations downward. We also find that downward expectation management is used to a greater extent than other tools such as real and accrual‐based earnings management. Additional analysis shows that the increase in expectation management is more pronounced for CEOs with lower general skills or shorter tenures, for firms with more independent boards, and for industries that are more homogeneous. Our path analysis suggests a significant link between increased use of expectation management after tightened non‐compete enforcement and meeting and beating earnings expectations, which in turn is linked to lower executive turnover. Overall, our findings suggest that expectation management is an important channel through which non‐compete enforcement reduces executive labor market mobility. Our study sheds light on the underlying mechanism through which labor market mobility affects disclosure choices and has important implications for both firms and regulators on the use and enforcement of non‐compete provisions.