Chapter 70 Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation

Heckman, James J.; Vytlacil, Edward

doi:10.1016/s1573-4412(07)06070-9

Cited by 471 publications

(412 citation statements)

References 128 publications

(227 reference statements)

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“…Greene, 2003;Heckman, 1979;Imbens and Wooldridge, 2009;Maddala, 1983;Rosenbaum and Rubin, 1983). One option with cross-section data is to use propensity score matching, which can control for a bias due to observable characteristics (Heckman and Vytlacil, 2007). However, TC adoption may also be influenced by unobserved factors, such as farmers' ability or agroecological conditions at the micro level.…”

Section: Model Specificationmentioning

confidence: 99%

Impact of tissue culture banana technology on farm household income and food security in Kenya

Kabunga¹,

Dubois

Qaim

2014

Food Policy

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in

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Section: Model Specificationmentioning

confidence: 99%

Impact of tissue culture banana technology on farm household income and food security in Kenya

Kabunga¹,

Dubois

Qaim

2014

Food Policy

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“…6 Due to the fact that we rely on previously developed methodology, detailed description of the propensity score method, its application in the evaluation as well as some methodological concepts utilized in the empirical section (such as average treatment effect of the treated) is not replicated in the paper to save the space. Readers requiring more details on the methodology could find Heckman and Vytlacil (2007a), Heckman and Vytlacil (2007b), Blundell and Costa-Dias (2008) or Gertler et al (2011) extremely helpful.…”

Section: Dataset and Empirical Strategymentioning

confidence: 99%

Ievaluation of Research and Development Tax Incentives Scheme in Croatia

Aralica

Botrić²

2013

Economic Research-Ekonomska Istraživanja

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According to the European Innovation Scoreboard metrics Croatia belongs to the group of moderate innovators, i.e. a country with below average innovation performance in comparison to the EU average in the period 2009-2010. Government subsidies are frequently introduced to improve countries' innovation performance. Whether existing R&D tax scheme in Croatia produces expected results is the key research question analyzed in the paper. Based on the microeconometric analysis of individual firms' data, we confirm positive effect of the subsidies on expenditures in research and development as well as on product innovation. However, the significant effect on process innovation is not found.

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“…56 Ziliak (2010). 57 Rothman et al (2008); Bruhn and Mackenzie (2009);Heckman and Vytlacil (2007);Ziliak (2010). 58 Student (1923); Gosset (1936);.…”

Section: The Power and Efficiency Of Balanced Over Randomized Fiementioning

confidence: 99%

W.S. Gosset and Some Neglected Concepts in Experimental Statistics: Guinnessometrics II

Ziliak

2011

J Wine Econ

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Student's exacting theory of errors, both random and real, marked a significant advance over ambiguous reports of plant life and fermentation asserted by chemists from Priestley and Lavoisier down to Pasteur and Johannsen, working at the Carlsberg Laboratory. One reason seems to be that William Sealy Gosset (1876–1937) aka “Student” – he of Student'st-table and test of statistical significance – rejected artificial rules about sample size, experimental design, and the level of significance, and took instead an economic approach to the logic of decisions made under uncertainty. In his job as Apprentice Brewer, Head Experimental Brewer, and finally Head Brewer of Guinness, Student produced small samples of experimental barley, malt, and hops, seeking guidance for industrial quality control and maximum expected profit at the large scale brewery. In the process Student invented or inspired half of modern statistics. This article draws on original archival evidence, shedding light on several core yet neglected aspects of Student's methods, that is, Guinnessometrics, not discussed by Ronald A. Fisher (1890–1962). The focus is on Student's small sample, economic approach to real error minimization, particularly in field and laboratory experiments he conducted on barley and malt, 1904 to 1937. Balanced designs of experiments, he found, are more efficient than random and have higher power to detect large and real treatment differences in a series of repeated and independent experiments. Student's world-class achievement poses a challenge to every science. Should statistical methods – such as the choice of sample size, experimental design, and level of significance – follow the purpose of the experiment, rather than the other way around? (JEL classification codes: C10, C90, C93, L66)

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Chapter 70 Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation

Cited by 471 publications

References 128 publications

Impact of tissue culture banana technology on farm household income and food security in Kenya

Impact of tissue culture banana technology on farm household income and food security in Kenya

Ievaluation of Research and Development Tax Incentives Scheme in Croatia

W.S. Gosset and Some Neglected Concepts in Experimental Statistics: Guinnessometrics II

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