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Purpose – This study investigates the effect of heterogeneity in an environment with a dynamic public bad.

Methodology/approach – Every period agents decide on own level of production that generates private revenue and emissions. Emissions lead to pollution that acts as a public bad and accumulates over time. Our treatment variable is the emission propensity of agents' production technologies. We characterize the Markov perfect equilibrium and social optimum and employ a laboratory experiment to compare the observed behavior to theoretical predictions.

Findings – We find that the observed production levels are between the Markov perfect equilibrium and social optimum. With experience, the strongest adjustment and lowest level of pollution is achieved in the heterogeneous treatment with high average emission propensity. When the costs of climate change are not severe, institutions are most necessary to create incentives for environmentally friendly behavior.

Research limitations/implications – The results of this study apply to the case when heterogeneity is exogenous and the only way to reduce emissions is by reducing production. Natural extensions include the option to invest in clean technologies, the availability of communication, the group size, and endogenously emerging and exogenous regulatory institutions.

Practical implications – Our results suggest that under relatively favorable conditions heterogeneous countries are less likely to achieve sustainability without external enforcement. Under unfavorable conditions the impending common threat of significant damage leads to higher levels of voluntary cooperation.

Originality/value of the chapter – This is the first study to address the practical problem of coordination among technologically diverse countries, and fundamental questions regarding the effect of heterogeneity in environments with a dynamic public bad.

Panel data provide the possibilities of estimating individual treatment effects for multiple individuals. Two issues are considered: (1) differences in the estimated individual treatment effects are due to heterogeneity or a chance mechanism? (2) what is the best way to estimate the average treatment effects? Testing and aggregation methods are suggested. Monte Carlo simulations are also conducted to shed light on these two issues. An empirical analysis on the involvement of underground organization in China’s Peer-to-Peer (P2P) activities through the “anti-gang” campaign is also provided.

This study investigates the economic outcomes of organic farming controlling for the four major aspects of a cropping system, including climate, genotypes, management and soil. Considering possible variations in treatment responses, this study also presents empirical evidence of heterogeneous treatment effects associated with spatial agglomeration or farm covariates.

Rice farm households data taken from the 2015 Agriculture Census is merged with township-level seasonal weather data, crop suitability index and average income per capita in Taiwan. To address the selection bias problem, the authors apply the Probit-2SLS instrumental variable (IV) method in the binary treatment model under homogeneous and heterogeneous assumptions.

It is found that organic farming leads to a significantly positive effect on rice farms' economic performances in terms of cost reduction and profit growth. This positive treatment effect is more sizable with spatial agglomeration. Furthermore, the treatment effect of organic farming is found to vary with the farm characteristics such as farmland area and the number of hired workers.

Two important implications for the promotion of sustainable agri-food production are inferred: (1) establishing organic agriculture specialized zones may benefit rural development; (2) providing economic incentives to small farms to expand their scale may be a more effective policy means to promote sustainable agri-food production.

The findings in this study complement the body of knowledge by drawing insights from the agriculture census data and providing profound evidence of the heterogeneous outcomes of organic farming due to spatial clustering and farm covariates.

The estimation of the effects of treatments – endogenous variables representing everything from child participation in a pre-kindergarten program to adult participation in a job-training program to national participation in a free trade agreement – has occupied much of the theoretical and applied econometric research literatures in recent years. This volume brings together a diverse collection of papers on this important topic by leaders in the field from around the world. This collection draws attention to several key facets of the recent evolution in this literature.

This study aims to evaluate the effectiveness of national and international R&D support programmes on firms’ technology scouting, defined as firms’ use of external knowledge sources.

Drawing on a unique data set on R&D support programmes for small and medium-sized enterprises (SMEs) operating in both manufacturing and service sectors across 28 European countries, this study reports treatment effects estimated by the copula-based endogenous switching model, which takes into account unobserved firm heterogeneity.

Empirical results indicate that R&D support programmes have heterogeneous effects on technology scouting. In particular, a crowding-out effect arises in the case of informal sources of external knowledge, whereas additional effects are reported for formal, strategic sources.

For informal sources of external knowledge, a random distribution of R&D measures would have a substantially larger effect rather than using current selection criteria.

To the best of the authors’ knowledge, this is the first study to explore the policy effects on technology scouting applying a copula-based endogenous switching model. Most cross-sectional empirical studies use matching estimators, although their main disadvantage is the selection on observables.

The purpose of this review article is to demonstrate how the quasi-experimental approach has been used to study environmental and natural resource issues related to agricultural production.

This review article first provides a short introduction to the quasi-experimental approach using the potential outcomes framework and then uses studies on the environmental sustainability of agricultural production to illustrate how quasi-experimental methods have been applied. Papers reviewed consist of studies that estimate the environmental externalities from agricultural production, evaluate agri-environmental and other related policies and programs, and demonstrate issues related to on-farm resource use and climate adaptation.

Difference-in-differences (DID) and two-way fixed effects methods that utilize the spatial and temporal variation in panel data are widely used to estimate the causal impact of changes in agricultural production and policy on the environment. Utilizing the discontinuities and limits created by agricultural policies and regulations, local treatment effects on land and other input use are estimated using regression discontinuity (RD) or instrumental variable (IV) methods with cross-sectional data.

Challenges faced by the food systems have made agricultural sustainability more critical than ever. Over the past three decades, the quasi-experimental approach has become the powerhouse of applied economic research. This review article focuses on quasi-experimental studies on the environmental sustainability of agriculture to provide methodological insights and to highlight gaps in the economics literature of agricultural sustainability.

In this chapter, the author argues that Austrians are perhaps uniquely placed to be effective practitioners of causal inference techniques on observational data. This is because, while the methods are easy to implement, their validity and value lies in a detailed, “analytical/historical” narrative to accompany the findings. This is true for several reasons. (1) all the models have identifying assumptions (e.g., no spillovers and parallel trends) that are best addressed by an exposition of the institutional/economic/historical milieu in place before and after the treatment under study; (2) determination of external validity also requires detailed institutional and historical knowledge; and (3) researchers often want to know the mechanisms producing the reduced form result that comes out of most causal inference studies. Here again, institutional and historical learning is crucial. My conclusion is that Austrians should add the tools of causal inference with observational data to their arsenal of analysis. This would be good both for their publication prospects and for the profession at large.

The combination of different knowledge sources has been considered conducive for innovation performance. While the literature has advanced regarding the combination of knowledge inputs as in internal and external research and development (R&D), the evolvement of knowledge blend from customers and competitors has also received substantial attention. The purpose of this paper is to delineate the sources of information from the customers into private and public and examine their direct effect on firm-level innovation. While the extant literature is mixed regarding this, no clear-cut results have emerged yet on the effect of knowledge combination from the private and public customers with internal R&D and human capital on innovation activities. This study, however, shed more lights on the inconclusiveness of the effect of knowledge diversity on firm-level innovation.

Using the microdata from the German Community Innovation Survey 2013, the authors employ a binary instrumental variable treatment model with Heckman selection, a suitable strategy to estimate binary variables to cope with a possible endogeneity issue.

The paper demonstrates that knowledge from customers in the private and public sector, and competitors are positively and significantly associated with innovation. The authors find evidence of a positive and significant effect of the combination of firm internal knowledge competencies with information from the public sector. In contrary, the blend of knowledge competencies with information from customers in the private sector and information from the competitors results in decline to innovation. The results also show that the blend of internal R&D with knowledge source from the customers in the public sector appears to have a stronger influence in the manufacturing sector than services. The results offer strong evidence of the positive link between knowledge diversity and firm-level innovation performance.

The results have significant managerial implications on the role of the blend of different sources of information in supporting a compelling internal knowledge development to optimise innovation performance.

This study is foremost to focus on knowledge sources from the customers in the public and private sector and its relationship with R&D and human capital in supporting a successful introduction of innovation.

Knowledge competencies and (R&D) activities are one of the most important sources of innovation and have been widely discussed in the literature. In comparison, the role of the competitive environment for the innovation activities of firms is still open to debate and has not been fully understood yet. Therefore, this paper intends to provide new evidence on the interaction between knowledge competencies and R&D activities of firms on the one side and their competitiveness in the market environment on the other. In particular, the moderating function of market competition is explored. In this respect, the analysis covers the main innovation types as well as both sectors, manufacturing and services.

The empirical analysis is based on a three years panel dataset of German manufacturing and service firms obtained from Mannheim Innovation Panel (MIP) and Community Innovation Surveys (CISs: 2011, 2013 and 2015). For the estimation, a binary instrumental variable treatment model with Heckman selection method is used. Also, it provides a suitable approach to estimating the binary variables in order to cope with endogeneity concerns.

The estimation results show that R&D activities and knowledge competencies are positively related to innovation activities of different types conditioned on firms' specific perception of their competitive environment, in terms of outdated products/services as well as strong competition from abroad. Most importantly, the results from the moderation estimation reveal that there is a significant difference between the manufacturing and service sector. Service firms engage more in internal R&D activities on generating product innovations while the manufacturing firms conduct more external R&D on specific types of innovation. Further, the authors find that strong competition from abroad positively and significantly reinforces the effect of knowledge competencies on innovation activities for more types in services than in manufacturing. In contrast, outdated products and services tend to decline the effect of knowledge competencies for some innovation types in both sectors. The authors also observe a positive and significant reinforcement effect on knowledge competencies. However, it is found more beneficial for service firms since they can employ more innovation strategies.

The focus of the study is mainly on the impact of firms' competitive environment on innovation activities in various types through its interaction with knowledge competencies and R&D activities, across manufacturing and service firms.

Contract farming (CF) is seen as a tool for creating new market opportunities hence increasing incomes for smallholder farmers. Critics, however, argue that CF is likely to pass risks to small scale farmers, thus favouring large scale farmers at the expense of smallholder farmers. The purpose of this paper is to examine the effect of CF on smallholder farmers’ income using a case study of avocado farmers in Kandara district in Kenya.

The study uses data collected from 100 smallholder avocado farmers in Kandara district in Kenya and employs an instrumental variable model (Probit-2SLS) to control for endogeneity in participation in the contract and examine the effect of CF on household, farm and avocado income.

The results indicate that participation in CF is not sufficient to improve household, farm and avocado income. Question remains regarding efficient implementation of CF arrangements to promote spill over effects on other household enterprises.

The research was carried out using farmers in Kandara district in Kenya as a case study, findings might therefore not reflect the status of CF in all countries.

The paper contributes to the growing debate on the effect of value chain upgrading strategies such as contracting on smallholder farmers’ welfare. The form of contracting studied in this paper differs from the standard contracts in that the key stakeholders (producers) are loosely enjoined in the contract through officials of their groups.