age group. Second, for some surveys the shares refer to sector of current employment rather that the sector of usual employment. I filter out the spurious data and the cleaned data set consists of more than 1,800 country-year observations spread across 150 countries. Using this data, I estimate distortions in Industry and Services relative to Agriculture. I smooth out the annual time series of distortions by averaging distortions in a decade and analyze the impact of changes in decennial distortions. There is a significant variation in distortions across countries with distortions at the 90<sup>th</sup> percentile being more than twice as large as distortions at the median. I also find that the distortions are higher in developing countries in both sectors. Moreover, the relationship between GDP per capita and distortions is statistically significant.2 The change in distortions realized by the median country over any two decades is small and distortions in any decade remains in the range of ±13% of the previous decade. However, countries located at the extreme report changes that are orders of magnitude larger than the modest change observed at the median. Interestingly, for many countries the distortions increase over the decades.

The benchmark quantitative exercises assume that labor shares remain constant over time within a country. In order to check the robustness to changing labor shares over time, I consider a case in which each sector experiences a differential change over decade and use the findings from Karabarbounis & Neiman (2014) to discipline the magnitude of change. The ability of changes in distortions in accounting for growth is essentially unchanged for the median country. Though, I find that the share of growth explained by changes in distortions increases for a few countries.

The paper is related to several strands of literature that study sectoral gaps in productivity. Closely related is the literature that explore the barriers to movement of labor out of agriculture (Todaro (1969), Bryan _et al._ (2014)). Another strand studies imperfections in credit markets that affect non-Agricultural sectors disproportionately driven by acute need of finance (Caballero _et al._ (2008), Buera _et al._ (2011), Song _et al._ (2011)). Credit market imperfections thus create hurdles for Industry and Services and stunt their growth leading to a depressed demand for resources. This work is also related to a large literature that tries to explain low agricultural productivity in poor countries (Restuccia _et al._ (2008), Adamopoulos (2011), Adamopoulos & Restuccia (2014), Gollin & Rogerson (2014) etc.). Finally, it also relates to the literature that argues that the measured gaps in productivity across sectors can be in large part explained by accounting for differences in human capital across sectors (Lagakos & Waugh (2013), Young (2013), Herrendorf & Schoellman (2015)). The measurement of labor inputs in this paper abstracts from differences in hours worked, human capital and talent across sectors due to the unavailability of time series data. Given the

> 2The estimates of distortions for the most recent decade are available for 84 countries. There is a large variation in GDP per capita across this sample with the country at 90<sup>th</sup> percentile being 15 multiples richer than the country at 10<sup>th</sup> percentile.

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