On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.     

Electricity supply preferences in Europe: Evidence from subjective well-being data

We use survey data for 139,517 individuals in 25 European countries, 2002–2011, to estimate the relationship between subjective well-being (SWB) and production shares of various electricity generation technologies. The estimated relationships are taken to represent preference relationships over attributes of electricity supply systems (costs, safety, environmental friendliness, etc.). Controlling for a variety of individual and macro-level factors, we find that individuals’ SWB varies systematically and significantly with differences in the electricity mix across countries and across time. Among other results, we find that a greater share of solar & wind power relative to nuclear power and electricity from coal and oil is associated with greater SWB at all levels of income and that the implied preference for solar & wind power over nuclear power has risen drastically after the Fukushima nuclear accident.     

A decision method for supplier selection in multi-service outsourcing

Although supplier selection in multi-service outsourcing is a very important decision problem, research concerning this issue is still relatively scarce. This paper proposes a decision method for selecting a pool of suppliers for the provision of different service process/product elements. It pioneers the use of collaborative utility between partner firms for supplier selection. A multi-objective model is built to select desired suppliers. This model is proved to be NP-hard, so we develop a multi-objective algorithm based on Tabu search for solving it. We then use an example to show the applicability of the proposed model and algorithm. Extensive computational experiments are also conducted to further test the performance of the proposed algorithm.     

Theoretical analysis and model design of search for ecological conservation redlines based on the sensitivity assessment of ecosystem services

Most small-scale social economies are characterised by their deficiency, lack, and/or difficulty in matching natural data. Against this backdrop, this paper builds a relatively uniform theoretical framework and designs a more economical and objective method for demarcating ecological conservation redlines (ECR) based on sensitivity assessment of ecosystem services. The results show that the sensitivity assessment model designed in this study can identify sensitive zones effectively, and that the ECR in Hubei Province are well within the sensitive zones so identified. The delimited areas based on the sensitive assessment of ecosystem services have great similarities (95%) with the actual ECR areas in Hubei Province. The most ecologically important functional zones (EIFZ) can also be identified using the regional ecological sensitivity coefficient. When the threshold of EIFZ is set higher, the probability that it falls within the ecologically sensitive areas is greater and the ECR delimited by the method proposed in this study will be more reliable. Theoretically, the delimitation of ECR can be inserted at any evaluation level with a grid resolution higher than that of the land use data, which can be used as a supplement to the ECR delimitation method in ecology or geography.     

Lumpy Investment and Corporate Tax Policy

In the presence of both convex and nonconvex capital adjustment costs in a dynamic general equilibrium model, corporate tax policy generates both intensive and extensive margin effects via the channel of marginal Q. Its impact is determined largely by the strength of the extensive margin effect, which, in turn, depends on the cross‐sectional distribution of firms. Depending on the initial distribution of firms, the economy displays asymmetric responses to tax changes. Moreover, an anticipated increase in the future investment tax credit reduces investment and adjustment rate initially.     

What drives technology transitions? An integration of different approaches within transition studies

This paper aims to provide a deeper understanding of transition drivers by reviewing four major strands of inquiry in transition studies: Multi Level Perspective (MLP); Strategic Niche Management (SNM); Transition Management (TM); Technological Innovation Systems (TIS). To the best of our knowledge, none of these contributions have so far provided a clear-cut classification of main drivers of transitions, as evidenced by the difficulty of practitioners in reaching goals as entrepreneurs, or policy makers in supporting economic growth. We believe that these theoretical streams share views relating the origin and drivers of transitions and that the analysis of the multi-level developments and systemic sub-processes by using the Integrative Propositional Analysis (IPA) allows for a more comprehensive identification of transition drivers. By mapping causal relationships within each perspective and by developing an integrative framework that takes in due account of overlaps between theories, we derived a new conceptual structure for the identification of transitions’ drivers.     

Analysing the provision of agricultural public goods: The case of irrigated olive groves in Southern Spain

Analysis of the joint production of private and public goods (PGs) by farming activities is a fertile research field. These joint production processes are typically characterised by a high level of complexity derived from the intense relationship between the production of both kinds of outputs. An integrated approach is strongly recommended for the study of the provision of agricultural PGs and the design of public intervention in this sector. Here, we propose a theoretical framework to apply an integrated approach using the analytic network process (ANP) to analyse the production of PGs by agricultural systems to support public decision-making concerning the design and implementation of agricultural policies. We introduce a novel approach in applying ANP along both directions of the influences among elements, allowing us to identify the most influenced PGs and the farmers’ most influential decisions. This methodological approach is empirically applied to a particular farming system: the irrigated olive groves (IOG) of Southern Spain. Results show that the PGs most influenced by olive growers’ decisions are soil fertility, the visual quality of agricultural landscapes and farmland biodiversity. In addition, the most influential factors affecting the provision of PGs are the structural ones, namely farm size and tree density, and, to a lesser extent, management factors dealing with fertilisation, soil and irrigation management. These results are useful for supporting agricultural policy decision-making to enhance adequate management of this farming system regarding PGs production.     

Major Psychological Factors Affecting Acceptance of New Breeding Techniques for Crops

New plant biotechnologies called new breeding techniques (NBT), which will follow the present genetically modified (GM) technology, have appeared and are attracting attention worldwide. The first purpose of this study was to show consumer attitudes toward traditional plant breeding, GM, and NBT crops. The second purpose was to verify the validity of a psychological model determining the acceptance of NBT crops. A survey was conducted in Japan with 657 randomly selected adult participants. The results showed that perceived risk, perceived benefit, trust, sense of bioethics, anxiety, and anger play an important role in the personal and public acceptance of NBT and indicated that trust and anxiety are especially important factors in both situations.     

Health and cosmetics: Investigating consumers’ values for buying organic personal care products

In investigating consumers’ intentions to re-purchase organic personal care products (PCP), this study extends the theory of planned behaviour by including perceived value dimensions as the antecedents of attitude in the model. The findings revealed that most of the hypothesised relationships linking the consumer perceived value constructs (namely, health, safety, hedonic and environmental) with attitude towards the rebuying of organic PCP, were supported. Also, better product knowledge about organic PCP would lead to more positive attitudes towards re-purchasing the product. In contrast, social value was not important in predicting attitude. Similarly, the influence of subjective norm on rebuying intention was not supported. In terms of ranking of importance with regards to prediction of re-purchasing intention, attitude was the most important predictor followed by perceived behavioural control, product knowledge, hedonic value, environmental value and safety value.     

How reliable and consistent are subjective measures of welfare in Europe and Central Asia?

This paper analyses the reliability and consistency of subjective well‐being measures, using the Life in Transition Survey. Drawing on two life satisfaction questions with alternative scales, our results do not reveal substantial biases in accounts of life satisfaction due to framing. Subjective individual assessments of household relative income position, on the other hand, do not appear to be reliable predictors of objective poverty or wealth. We find that subjective relative income position is only weakly correlated with objective welfare measures. There are differences in evaluations of the household's relative standing across different household members, and these differences are correlated with respondent characteristics.