Methodology

China Pathfinder uses data provided by a range of sources and applies in-house calculations to original data for viewers’ better understanding. For more details on our data scores and methodology for each annual indicator, see below.

Financial System Development

Efficient Pricing of Credit: Average annual corporate borrowing rate data from IMF International Financial Statistics, European Central Bank, and Bank of England; GDP deflator data from the World Bank; projected GDP growth rates data from the IMF World Economic Outlook (annual average calculated from quarterly reports). Differences between the interest rates and projected growth rates are shown in absolute value for visualization purposes. The calculation used is as follows: Average annual interest rate for loans to non-financial corporations, subtracting the average of the projected GDP growth rate in the current and following year.

Direct Financing Ratio: Equity: Data from Bloomberg and World Bank. The total market capitalization is a calculation of the country’s aggregated value of listed companies’ shares of stock. The measure is then divided by the country’s GDP for the same year.

Direct Financing Ratio: Debt: Data from the World Bank Global Financial Development collection and Bank of International Settlements (BIS). The ratio was calculated by dividing the value of total outstanding debt securities in the latest year by the country’s nominal GDP. South Korea’s outstanding debt securities data are the sum of domestic and international securities data, as opposed to aggregated total data, which risk double counting.

China’s State Presence in Financial Institutions Banking Assets Controlled by Private Firms: Data from Bloomberg, China Pathfinder calculations. This indicator reflects the degree to which China’s financial system is controlled by government-owned institutions. For each of the top ten financial institutions, we use the percent of shares owned by the government, then take the weighted average of the institutions’ percentages based on institution market capitalization. This in-house constructed indicator replaces data from the World Bank’s Bank Regulation and Supervision Survey (BRSS), which updates only every few years.

Financial Institutions Depth Index: Data from the IMF, China Pathfinder estimates. This indicator captures bank credit to the private sector, the assets of the mutual fund and pension fund industries, and the size of life and non-life insurance premiums. This indicator is a useful proxy for the sophistication of the financial system in terms of financial offerings available beyond the banking system. Our 2021 data points are extrapolated from the IMF’s 2020 dataset.

Financial Market Access Index: Data from the IMF, China Pathfinder estimates. This indicator combines two variables: (1) the percentage of market capitalization outside of top 10 largest companies to proxy access to stock markets; and (2) bond market access, estimated as the number of financial and non-financial corporate issuers on the domestic and external debt market in a given year per 100,000 adults. This indicator illustrates the difficulties in accessing the stock market by smaller companies and also captures the number of issuers in the bond market. Our 2021 data points are extrapolated from the IMF’s 2020 dataset.

Market Competition

Market Concentration: Data from Bloomberg, China Pathfinder calculations. The market concentration indicator takes the simple average of data from 11 sectors as categorized by Bloomberg: communications, consumer discretionary, consumer staples, energy, financials, healthcare, industrials, materials, real estate, technology, and utilities. The industry categorization is consistent across all countries in the sample. The indicator measures the percentage of each sector’s revenue that the top five companies of that sector make up. If five firms make up a higher percentage, then the market is considered more concentrated and less competitive. For sectors with less than 50 listed companies total, the top 10 percent of companies are used (for instance, we use the top 3 firms in calculating share of total sector revenue if the sector has only 30 listed firms.) This indicator replaced the Herfindahl-Hirschman Index, which is updated on a 1-year lag or more.

Rule of Law: Data from the World Bank’s Worldwide Governance Indicators (WGI), China Pathfinder estimates. The Rule of Law Index reflects perceptions of the extent to which agents have confidence in and abide by the rules of society—in particular, the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. We adjust the original range of -2.5 to 2.5 to one of 0 to 5 for the purpose of data visualization. Our 2021 data points are extrapolated from the World Bank 2020 dataset.

FDI Openness Index: Data from the OECD’s FDI Regulatory Restrictiveness Index, China Pathfinder estimates. It measures statutory restrictions on FDI in twenty-two economic sectors, as follows: agriculture, forestry, fisheries, mining & quarrying (including oil extraction), food and other, oil refinery and chemicals, metals, machinery and other minerals, electric, electronics and other instruments, transport equipment, electricity, construction, wholesale, retail, media, communications, banking, insurance, other finance, business services, and real estate investment. Our index deliberately excludes transportation and hotels and restaurants sectors. We use an inverse version of the original index. Our 2021 data points are extrapolated from the OECD’s 2020 dataset.

Scope of SOEs Index: Data from the OECD 2018 Product Market Regulation Database. We take data directly from the OECD. The Scope of SOEs Index measures the degree to which states maintain SOEs in a broad array of different industries. The index ranges from 0–6, with 0 meaning the state maintains no SOEs in any industry category and 6 meaning the state maintains SOEs in all industry categories included in the calculation.

Proportion of SOEs in Top 10 Companies, All Sectors: Data from Bloomberg and Chinese official sources. This indicator was constructed in-house and replaces the Scope of SOEs Index, as the OECD 2018 Product Market Regulation (PMR) Database is no longer updated. The indicator defines an SOE as a company where the government holds at least a 50 percent share. The top 10 companies are determined by firms that have the highest market capitalization in their respective sectors. The outcomes (state-owned or not) for each company are then weighted according to the company’s respective market capitalization. The process is applied across 11 industries: communications, consumer discretionary, consumer staples, energy, financials, healthcare, industrials, materials, real estate, technology, and utilities.

Modern Innovation System

National Spending on Innovation: Data from UNESCO Institute for Statistics and OECD. This indicator looks at total R&D expenditures as a percentage of GDP to ensure that those expenditures are roughly comparable regardless of a country’s aggregate economic activity levels.

Venture Capital Attractiveness: Data from Pitchbook and World Bank. This indicator expresses total venture funding in an economy as a share of its total GDP. Venture funding invested totals are originally in USD million, and the criteria are as follows: completed deals of all VC stages, and the transaction date falls within the 2021 timeframe (or 2010 for the country benchmarks).

Private vs State-Funded Innovation: Data from the OECD, Australian Bureau of Statistics, China Pathfinder calculations. This ratio is calculated by dividing total business enterprise spending by government spending on domestic R&D. Our 2021 data points are extrapolated from the OECD’s 2020 dataset.

Total Triadic Patent Families Filed: Data from OECD, Patents by main technology and by International Patent Classification (IPC), China Pathfinder estimates. A triadic patent family is a defined set of patents registered in various countries to protect the same innovation. Triadic patent families are filed at three of these major patent offices: the European Patent Office (EPO), the Japan Patent Office (JPO), and the United States Patent and Trademark Office (USPTO). We take the simple count of triadic patent families filed by country provided by the OECD and divide it by each country’s respective GDP (in millions USD) to adjust the count by the size of that country’s economy. Extrapolation and estimation are used where patent data extends through only 2019.

International Attractiveness of a Nation’s Intellectual Property: Data from the International Monetary Fund, Balance of Payments Statistics Yearbook and data files; and CEIC for GDP data. We divide charges for the use of intellectual property, receipts (BoP, current US$) data provided by the IMF by 2021 GDP data from CEIC.

Strength of Intellectual Property Protection Measures: Data from the US Chamber of Commerce Global Intellectual Property Center. The index is composed of fifty individual indicator scores that look at both existing regulations and standards, as well as their enforcement. The index series began in 2012, so we used 2012 index results as a proxy for the countries’ 2010 benchmarks.

Trade Openness

Goods Trade Intensity of the Economy: Data from the OECD Balance of Payments, China Pathfinder calculations. We calculated the sum of goods debits (imports) and goods credits (exports) country data totals for each year to calculate two-way goods trade for our selection of countries. For the global total two-way goods trade, the same process was used, but for global goods imports and exports totals. The final step was to divide the former by the latter.

Services Trade Intensity of the Economy: Data from the OECD Balance of Payments, China Pathfinder calculations. We calculated the sum of services debits (imports) and services credits (exports) country data totals for each year to calculate two-way services trade for our selection of countries. For the global total two-way services trade, the same process was used, but for global services imports and exports totals. The final step was to divide the former by the latter.

Tariff Rates: Data from the World Bank. The Simple mean MFN tariff rate is the unweighted average of MFN rates for all products subject to tariffs calculated for all traded goods. We use the simple average tariff rate because the weighted average could skew the outcome if certain countries had high product-import shares corresponding to limited partner countries.

Services Trade Openness Index: Data from the OECD. The Services Trade Restrictiveness Index measures policy restrictions on traded services across four major sectoral categories. These are logistics, physical, digital, and professional services. Each sectoral category also contains several specific industry subindices. We take the average of all four sectoral category indices to create our combined STRI index. Values are inverted from the original OECD index, creating the Services Trade Openness Index.

Digital Services Trade Openness: Data from the OECD. We inverse the original index so that lower values on the index indicate more restrictions to digital trade (or less openness). The DSTRI measures barriers that affect trade in digitally enabled services across fifty countries. This includes policy areas such as infrastructure and connectivity, electronic transactions, payment systems, and IP rights.

 

Direct Investment Openness

Inward FDI Intensity of the Economy: Data from the IMF. We look at inbound FDI stock data from the IMF and divide it by 2021 annual GDP for each sample country to create this indicator. The result demonstrates the relative size of inward FDI flows.

Outward FDI Intensity of the Economy: Data from the IMF. We look at outbound FDI stock data from the IMF and divide it by 2021 annual GDP for each sample country to create this indicator. The result demonstrates the relative size of outward FDI flows.

Inward Direct Investment Restrictiveness: Data from China Pathfinder, Rhodium Group, and IMF Annual Report on Exchange Arrangements and Exchange Restrictions. This indicator captures (1) foreign investment reviews; (2) sectoral and operational restrictions; (3) repatriation requirements and other foreign exchange restrictions. Based on these measures and proprietary data, we create a 0-10 scoring system where 0 represents no restrictions. Low, medium, high, and total restrictions are assigned increasing numeric values up to 10.

Outward Direct Investment Restrictiveness: Data from China Pathfinder, Rhodium Group, and IMF Annual Report on Exchange Arrangements and Exchange Restrictions. This indicator captures (1) foreign investment reviews; (2) sectoral and operational restrictions; (3) repatriation requirements and other foreign exchange restrictions. Based on these measures and proprietary data, we create a 0-10 scoring system where 0 represents no restrictions. Low, medium, high, and total restrictions are assigned increasing numeric values up to 10.

Portfolio Investment Openness

Portfolio Investment Volumes: Debt: Data from the IMF International Financial Statistics. This indicator shows the internationalization of bond markets. It is calculated by adding assets and liabilities of portfolio investment debt securities, and dividing this sum by GDP.

Portfolio Investment Volumes: Equity: Data from the IMF International Financial Statistics. This indicator shows the internationalization of equity markets. It is calculated by adding assets and liabilities of equity and investment fund shares, and dividing this sum by GDP.

Inward Portfolio Investment Restrictiveness: Data from the IMF AREAER annual reports, China Pathfinder. This is a proprietary indicator that measures de jure restrictions on cross-border purchase and issuance of debt and equity securities based on information presented in the IMF’s annual AREAER reports. It covers the purchase of local securities by non-residents and the issuance of overseas securities by residents. It does not cover repatriation or surrender requirements. Based on these measures and proprietary data, we create a 0-10 scoring system where 0 represents no restrictions. Low, medium, high, and total restrictions are assigned increasing numeric values up to 10.

Outward Portfolio Investment Restrictiveness: Data from the IMF AREAER annual reports, China Pathfinder. This is a proprietary indicator that measures de jure restrictions on cross-border purchase and issuance of debt and equity securities based on information presented in the IMF’s annual AREAER reports. It covers the purchase of overseas securities by residents and the issuance of local securities by non-residents. It does not cover repatriation or surrender requirements. Based on these measures and proprietary data, we create a 0-10 scoring system where 0 represents no restrictions. Low, medium, high, and total restrictions are assigned increasing numeric values up to 10.