beyond a certain employment threshold, yet any of these measures tends to explain only a small fraction of misallocation.

Conversely, regulatory restrictions to movements across space appear to play a more important role. Tombe and Zhu (2015) study the impact of goods- and labor-market frictions using a general equilibrium model calibrated with Chinese data. Overall the reduction in trade and migration frictions explain almost 50% of productivity growth in 2000-2005, and the fall in internal trade and migration costs contributed about 20%.

Other studies of China examine also state-owned enterprises, their preferential access to resources, and the related productivity losses (e.g., Song, Storesletten and Zilibotti (2011)). Brandt, Tombe, and Zhu (2013) study the period 1985-2007 and find that within-province misallocation of capital between state and nonstate sectors reduced the nonagricultural TFP growth rate by 0.5% per year. The costs of misallocation appear to have sharply increased during the latest period analyzed, 1997-2007.

**Property rights.** Property rights affect resource allocation and therefore productivity, by limiting expropriation and facilitating market transactions (Besley and Ghatak (2010)). Adamopoulos and Restuccia (2014) assess the impact of the Comprehensive Agrarian Reform Program (CARP) on agricultural productivity by calibrating a model with data from the Philippines.<sup>4</sup> In 1988, the reform introduced ceilings on existing land holdings, promoted transfer of above-ceiling land to landless and smallholders, and restricted the transferability of the redistributed land. Between 1989 and 1993, agricultural productivity fell by more than 10%. According to the model, this decline is the result of distortions in farm size and occupational choices, as land is transferred from more to less productive holders.

**Trade and competition.** Trade policy influences the allocation of resources across heterogeneous producers and consequently impacts aggregate productivity. Two approaches are used to quantitatively assess the impact of tariffs and/or other distortionary forms of protection. On the one hand, evidence comes from model-based estimates. For example, building on Arkolakis, Costinot, and Rodríguez-Clare (2012), Edmond, Midrigan, and Xu (2015) study the impact of moving from autarky to free trade by calibrating a model to Taiwanese manufacturing data. Opening to trade leads to greater competitive pressure and substantially reduces markup distortions. Consequently, it reduces misallocation and improves total factor productivity by more than 12%.

On the other hand, specific trade policy changes are examined for causal inference. Khandelwal, Schott, and Wei (2013) study the elimination of externally imposed quotas on Chinese textile and clothing exports. Interestingly, the distortionary effects of the quotas imposed by the United States, Canada and European Union were compounded by the effects of government-imposed quotas allocated in favor of (less productive) state-owned enterprises. <u>The authors find that 71% of the productivity gains derived from the empirical analysis are</u>

> 4 Incidentally, it is interesting noting that models tend to explain a larger share of the changes in agricultural rather than manufacturing productivity.

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