Exact interpretation of dummy variables in semilogarithmic equations

Garderen, Kees Jan van; Shah, Chandravadan

doi:10.1111/1368-423x.00078

Cited by 185 publications

(113 citation statements)

References 8 publications

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“…Rather than focusing on the point estimate alone, we are interested also in the (95%) confidence interval of Δφ i j,k , taking into account (i) the imprecision of the point estimates in Tables 2, 3, and 5 and (ii) the fact that the considered trade cost measures which we change in counterfactual equilibrium are binary which requires adjusted confidence intervals (see van Garderen and Shah 2002). van Garderen and Shah (2002) prove that for an impact estimate of the k − th binary (in our case, trade cost) variable t i j,k in percent, switching that variable with estimated parameter α k from zero to unity obtains …”

Section: Data and Estimation Resultsmentioning

confidence: 99%

A generalized spatial error components model for gravity equations

Egger

Pfaffermayr

2015

Empir Econ

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Since the publication of the paper by Anderson and van Wincoop (J Econ Litt 42:691-751, 2004), the estimation of gravity models has turned increasingly structural. The benefit of this development is that empirical models which are based on few parameters explain data on bilateral trade flows relatively well, while being consistent with general equilibrium. The latter permits using the estimated parameters for comparative static analysis. In general, in the cross section such models involve country-pair-specific variables and exporter-specific as well as importer-specific variables. The latter are determined through structural model constraints. The disturbances on this model are typically assumed to be independently if not also identically distributed. This paper illustrates that the assumption of independently distributed disturbances is likely flawed in practice. Ignoring such independence leads to inconsistent test statistics and standard errors of the parameters. We present a structural gravity model which permits the disturbances to be cross-sectionally interdependent in up to three dimensions and illustrate the consequences of doing so for inference.

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Section: Data and Estimation Resultsmentioning

confidence: 99%

A generalized spatial error components model for gravity equations

Egger

Pfaffermayr

2015

Empir Econ

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“…The 6 We calculate home market advantage using 100 · (exp(ĉ) − 1), whereĉ is the coefficient on the dummy for being a home brand. If we follow Kennedy (1981) and van Garderen and Shah (2002) and calculate home market advantage using 100 · (exp(ĉ − 1 2 V (ĉ)) − 1), where V (ĉ) is the estimate of its variance, we obtain nearly identical results, since the coefficient is very precisely estimated.…”

Section: Data and Descriptive Evidencementioning

confidence: 92%

What Drives Home Market Advantage?

Coşar¹,

Grieco²,

Li³

et al. 2015

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In the automobile industry, as in many tradable goods markets, firms usually earn their highest market share within their domestic market. The goal of this paper is to disentangle the supplyand demand-driven sources of the home market advantage. While trade costs, foreign production costs, and taste heterogeneity all matter for market outcomes, we find that a preference for home brands is the single most important driver of home market advantage -even after controlling for brand histories and dealer networks. Furthermore, we also find that consumers favor domestically producing brands regardless of the historical brand origin.A. Kerem Cosar

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“…The robustness checks show that the difference in spending on education holds across various specifications. An exact interpretation of dummy variables in semi-logarithmic regressions is provided in the row "Transformation" following van Garderen and Shah (2002). However, the exact interpretation deviates from the regression coefficients only slightly and also statistical significance remains unchanged.…”

Section: Total Causal Effectmentioning

confidence: 99%

“…Standard errors clustered at the household level in parenthesis. The line "Transformation" reports approximate unbiased estimator of the percentage change of a dummy variable in a semi-logarithmic regression (Kennedy 1981) and its standard error following van Garderen and Shah (2002).…”

Section: Total Causal Effectmentioning

confidence: 99%

Displacement and education of the next generation: evidence from Bosnia and Herzegovina

Eder

2014

IZA J Labor Develop

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In this paper, I study the effect of displacement (in the sense of forced migration) of parents during a violent conflict on investment in their childrens' education years later. Using the ethnic division during the Bosnian War as a natural experiment, I plausibly identify exogenously displaced households and compare them to households who did not have to move because of the war. Displaced parents spend between 20 and 30% less on the education of their children in primary and secondary school. The result also holds for single expenditure positions like textbooks, school materials and annual tuition in secondary school. A number of robustness checks and nearest-neighbor matching is performed to confirm the finding. A decomposition of the causal effect shows that differences in income and the stock of durable goods can at most explain one third of the finding. Potential explanations for the reduced spending of displaced parents on education include altered preferences through the exposure to violence, increased uncertainty about the future, and financial constraints. JEL Classification: I25; J15; O15

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Exact interpretation of dummy variables in semilogarithmic equations

Cited by 185 publications

References 8 publications

A generalized spatial error components model for gravity equations

A generalized spatial error components model for gravity equations

What Drives Home Market Advantage?

Displacement and education of the next generation: evidence from Bosnia and Herzegovina

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