Barriers to Entry and Development*

Herrendorf, Berthold; Teixeira, Arilton

doi:10.1111/j.1468-2354.2011.00639.x

Cited by 65 publications

(39 citation statements)

References 63 publications

(122 reference statements)

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“…In particular, both predict a large wage gap between agricultural and non-agricultural workers, as in the data. This is in contrast to other papers in the literature, which reconcile this wage gap using some sort of exogenous barrier to workers moving out of agriculture (e.g., the work of Caselli and Coleman 2001;Restuccia, Yang, and Zhu 2008;Adamopoulos and Restuccia 2011;Tombe 2011;and Herrendorf and Teixeira 2011). Both are also quantitatively consistent with the higher employment shares in agriculture in poor countries, and the higher relative prices of agricultural goods in poor countries.…”

supporting

confidence: 45%

“…Agricultural Wage Gaps.-One novel prediction of our model is that average wages are much lower in agriculture than non-agriculture even though there are no barriers to workers moving between sectors (as in the models of Caselli and Coleman 2001;Restuccia, Yang, and Zhu 2008;Herrendorf and Teixeira 2011;Adamopoulos and Restuccia 2011;and Tombe 2011). In our model, this agricultural wage gap is Note: Expected individual productivity relative to the population means are calculated as E( z a | z a / z n > 1/ p a )/E( z a ) and E( z n | z n / z a > p a )/E( z n ) and represent the conditional average individual productivity in agriculture and non-agriculture relative to the unconditional average productivities.…”

Section: E Assessment Of Calibrated Model's Cross-country Implicationsmentioning

confidence: 98%

“…When calibrated, the extended model produces four times as much variation in productivity in agriculture as non-agriculture. The improved performance comes from the well known role that land plays as a fixed factor in agriculture (e.g., the models of Restuccia, Yang, and Zhu 2008;Adamopoulos and Restuccia 2011;and Herrendorf and Teixeira 2011). While the importance of selection is similar in magnitude as in the benchmark model, decomposing the results into the contribution from land versus selection shows that selection is as important or more than the effects from land alone.…”

mentioning

confidence: 93%

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Selection, Agriculture, and Cross-Country Productivity Differences

Lagakos

Waugh

2013

American Economic Review

279

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Cross-country labor productivity differences are larger in agriculture than in non-agriculture. We propose a new explanation for these patterns in which the self-selection of heterogeneous workers determines sector productivity. We formalize our theory in a generalequilibrium Roy model in which preferences feature a subsistence food requirement. In the model, subsistence requirements induce workers that are relatively unproductive at agricultural work to nonetheless select into the agriculture sector in poor countries. When parameterized, the model predicts that productivity differences are roughly twice as large in agriculture as non-agriculture even when countries differ by an economy-wide efficiency term that affects both sectors uniformly. (JEL J24, J31, J43, O11, O13, O40) Cross-country labor productivity differences are much larger in agriculture than in the non-agricultural sector (Caselli 2005; Restuccia, Yang, and Zhu 2008). Because developing countries have most of their workers in agriculture, their low productivity in agriculture accounts for nearly all of their low productivity in the aggregate. This implies that understanding why productivity differences in agriculture are so large compared to those of the non-agricultural sector is at the heart of understanding world income inequality. 1 In this article we propose a new explanation for these productivity patterns in which the self-selection of heterogeneous workers determines sector productivity. We start from the well-known idea that in poor countries, where economy-wide efficiency is low, most people must work in the agricultural sector in order to satisfy subsistence consumption needs. This is what Schultz (1953) famously called the "food problem." Our insight is that precisely because the majority of workers in 1 Versions of this argument have been made by Caselli (2005); Restuccia, Yang, and Zhu (). For helpful comments we thank the three anonymous referees,

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supporting

confidence: 45%

Section: E Assessment Of Calibrated Model's Cross-country Implicationsmentioning

confidence: 98%

mentioning

confidence: 93%

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Selection, Agriculture, and Cross-Country Productivity Differences

Lagakos

Waugh

2013

American Economic Review

279

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“… See Parente and Prescott (1999),Holmes and Schmitz (1995),Krusell and Ríos-Rull (1996) andHerrendorf and Teixeira (2010).4 For the functional form α ¼ 1 Àðκ=AnpÞþðn f =npÞ (where α is bounded above by 1), the two cases are equivalent.B. Bridgman / Journal of Economic Dynamics & Control 52 (2015) 136-149…”

mentioning

confidence: 96%

Competition, work rules and productivity

Bridgman

2015

Journal of Economic Dynamics and Control

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a b s t r a c t I develop a theory to explain why workers want restrictive work rules, those that induce wages to be paid for non-productive labor hours, and why competition reduces them. Work rules allow workers to maintain both high levels of employment and wages. They generate a fixed payment that transfers the firm's surplus to workers, which wages alone cannot do, making them robust to alternative modeling assumptions. Competition loosens work rules by reducing the firm's surplus, which increases productivity.Published by Elsevier B.V.

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“…On the one hand, a reduction in trade costs provides larger business opportunities for the most productive plants, which are able 22 Recent papers have emphasized the importance of entry costs in explaining differences in income levels and growth. Barseghyan and DiCecio (2001) and Herrendorf and Teixeira (2011) quantify the effects of entry costs on aggregate TFP and income in developing countries. Nicoletti et al (2003) show that differences in the regulation of entry explain the productivity growth divergence between continental Europe and the US during the 1980s and the 1990s.…”

Section: A Look On Particular Distortionsmentioning

confidence: 99%

Distortions and the size distribution of plants: evidence from cross-country data

García-Santana

Ramos

2015

SERIEs

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We study the relationship between economic distortions and the size distribution of plants using comparable plant-level data across 104 developing countries. Our main result is to show that, other things equal, countries with larger economic distortions allocate more labor to small unproductive units. By decomposing the business environment into different type of distortions, we find that poor access to financial credit is the one driving our results. We also show that there exists a significant crosscountry relationship between the size distribution and aggregate productivity. These results are consistent with a large recent literature on misallocation of resources across firms.

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Barriers to Entry and Development*

Cited by 65 publications

References 63 publications

Selection, Agriculture, and Cross-Country Productivity Differences

Selection, Agriculture, and Cross-Country Productivity Differences

Competition, work rules and productivity

Distortions and the size distribution of plants: evidence from cross-country data

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