rafmacalaba/datause-encoder-data huggingface dataset:
This research uses _A Survey of State Enterprises: 1980--1989,_ a retrospective survey conducted by the Chinese Academy of Social Science in 1991. The data set is a balanced panel design: no firms were dropped out during the 10 years.<sup>3</sup> Survey questionnaires were sent out by the provincial System Reform Commissions to 800 state enterprises. Valid responses from 769 firms, located in 21 cities in four provinces of China (Sichuan, Jiangsu, Jilin, and Shanxi), were received. The data set was not designed to be a random sample of the state enterprises: making up more than 70% of the sample, large firms were over-represented. The median firm of the sample had 931 employees.

The data set consists of two parts. Part one, intended to be completed by the accountant of the firm, contains quantitative tables with details of the firm's production inputs, outputs, internal incentives, wages, labor composition, and profit distributions between the govenmment and the firn. Part two, to be completed by the manager, contains information on the firm's industry affiliation, age, and size; the contract terms of the manager; the relationship of the firm to the government; when the firm was granted the discretion to plan output levels and what to produce, whether the manager had the discretion to determine wages; the share of the firm's input from subsidized state sources, from the market, and from bartering with other firms, etc. It also has information about how value added was distributed, and how the decentralized reforms evolved over time.

During the 1980s, the Chinese government experimented with decentralizing SOEs to boost productivity. By the end of the decade, those state enterprises had a much different legal structure, and became much more, though not completely, marketoriented.<sup>4</sup> Both the productivity level and input uses of firms changed over this period. The average labor productivity of the firms in the data set increased at 2.6% annually.

> 2This data set has been used by many other authors, including Groves et al. (1994, 95).

> _3In_ the 1980s the Chinese SOEs did not face a real threat of bankruptcy.

> 4See Johnson (1990), Tidrick et al. (1987), Perkins (1994), and Jefferson and Rawski (1994) for more thorough coverage of industrial reforns and the rural reformns of China.

3
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19 quantitative measures of financial stability (see, e.g., Bank of England 2012). This does not mean that existing approaches completely overlook incentives- related issues.

One possibility is for the incentive audits to be done as part of the financial sector assessments carried by third-party assessors, such as those done under the Financial Sector Assessment Program by the IMF and World Bank. This would be in line with an earlier proposal by Chai and Johnston (2000). Indeed much of the information required to conduct an incentive audit is already collected or can be collected as part of assessments of financial systems. The FSAPs already examine the structure of financial systems, and the adequacy of safety nets and crisis management arrangements; and the codes and standards assessments as part of FSAPs review the independence, resources and accountability of supervisory bodies. In addition, international regulatory reforms developed by the FSB are encouraging increased attention to unregulated entities, the adequacy of information disclosures and corporate governance and compensation practices.

The idea of incentive audits therefore is not to build a new assessment from scratch, but to raise the profile of incentive-related issues and bring more structure to the assessments. The incentive audits could be considered as an organizing framework that puts at its center the identification of perverse incentives. Incentive audits need to be combined with quantitative risk assessment, which helps to identify near-term vulnerabilities (as exemplified in the so-called “risk assessment matrix” used in recent FSAP assessments) and with assessments of the regulatory, supervisory, and crisis preparedness frameworks (which, in the context of the FSAP, include assessments of compliance with international standards).

Incentive audits could of course be a very helpful tool also at the national level and could be performed by a body or agency within a country. The obvious choice is the macroprudential authority, which could use incentive audits to complement the other instruments available to country authorities.

As regards the tools that the macroprudential authority would use, these would include micro prudential instruments tailored to address systemic risks, but would also encompass a broader set of instruments to deal with the sources of incentive failures. Table 1 lists a number of the possible instruments and their role in addressing incentive problems that give rise to systemic risk.

**Table 1. Instruments to Address Incentive Problems**

|**Tools for addressing systemic risk **|**Purpose**|
|---|---|
|Micro prudential tools (capital and liquidity<br>requirements, provisioning and collateral<br>policies)|1. To address externalities that are not internalized<br>in the risk assessments of financial firms and<br>markets and create systemic risk, including risks<br>from size, interconnections, and lack of<br>substitutability;|
# 1 Introduction

To measure the trade restrictiveness of a country’s trade policy regime, one needs to overcome two important aggregation hurdles: aggregation of different forms of trade policies and aggregation across goods with very different economic importance.

Regarding the fi rst aggregation problem, trade policy can take many different forms: tariffs, quotas, non-automatic licensing, antidumping duties, technical regulations, monopolistic measures, subsidies, etc. How can one summarize in a single measure the trade restrictiveness of a 10 percent tariff, a 1000 tons quota, a complex non-automatic licensing procedure and a $1 million subsidy? Often the literature relies on outcome measures, e.g., import shares. The rationale is that import shares summarize the impact of all these trade policy instruments. The problem is that they also measure differences in tastes, macroeconomic shocks, and other factors, which should not be attributed to trade policy. Another approach that is also often followed is to simply rely on tariff data and hope that all other instruments are (perfectly) correlated with tariffs. These are obviously unsatisfactory solutions. A more adequate approach to solve this fi rst problem is to bring all types of trade policy instruments into a common metric.<sup>1</sup> Regarding the second aggregation problem, trade policy is set at the tariff line level and there are often more than 5000 tariff lines in a typical tariff schedule. How can one summarize all this information in one aggregate and economically meaningful measure? Commonly used aggregation procedures include simple average, import-weighted averages and frequency or coverage ratios; none of which has a sound theoretical basis. For example, imports subject to high protection rates are likely to be small and therefore will be attributed small weights in an import-weighted aggregation, which would underestimate the restrictiveness of those tariffs. In the extreme case, goods subject to prohibitively high tariffs have the same weight as goods subject to zero tariffs: a zero weight. Similarly, when computing simple average tariffs, very low tariffs on economically meaningless goods

> 1 This is, for example, what the IMF’s trade restrictiveness index does by implementing the following procedure. First, countries with an average tariff below a certain threshold are open and therefore score only 1 point, whereas countries with higher average tariffs score a higher number of points. Second, countries with a share of tariff lines affected by non-tariff barriers below a certain threshold are open and score 1 point, and countries with higher shares score a higher number of points. So for example, an average tariff of 3 percent scores 1 point and when only 5 percent of tariff lines are affected by NTBs the country also scores 1 point, for a total of 2 point on the TRI. Different types of trade policy instruments have been brought to a common metric. The problem is that it is not clear why a 3 percent average tariff should be equivalent to a 5 percent NTB coverage. These are ad-hoc criteria with no economic basis.
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-3-

grouped into three categories according to judgments on the antiexport bias before adjustment lending for each country: low, medium, or high.<sup>4</sup> Sufficiently large differences were detected to permit such a broad classificztion. Only Chile and Korea had a relatively low level of restrictions: 60 percent had a high level, and 35 percent had a medium level.

A comparison with trade restrictiveness in developed countries helps to put the initial restrictions in developing countries In broader perspective. The weighted average tariff rate for fifty developing countries was 26 percent at the end of 1985 according to Erzan et al. (1966). Adding other import charges raises the figure to 34 percent. For OECD countries average tariffs on industrial goods were estimated to be about 5 percent according to a 1980 GATT report and Finger and Laird (1987) and are roughly of that order today. Erzan et al. estimated the coverage of nontariff barriers in the same fifty developing countries to be 40 percent (unweighted) of import items corresponding to all tariff positions at the end of 1985. Finger and Laird provide a similar estimate for thirty-eight developing countries for 1982. They also estimated that 15 percent of the product categories of the eleven industrial countries in their sample were subject to nontariff barriers in 1984. Laird and Yeats (1988) provide a similar figure (15.9 percent) for all products in fourteen industrial countries in 1986.5 While the intent and influence of tariffs a-d nontariff b&rriers must be interpreted individually for each country, these estimates indicate that developing countries, on the whole, have a much more restrictive trade regime than do developed countries.
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