About China Pathfinder


The China Pathfinder Project is a collaboration between the Atlantic Council and Rhodium Group to track China’s convergence or divergence from open market-economy norms. This project is nonpartisan, and seeks to foster consensus about where China stands in relation to advanced market economies. With that goal in mind, our design balances accessibility for nontechnical readers with commitment to robust, transparent, data-grounded methods.

Research Framework

The China Pathfinder Project evaluates the economic system of China and ten open market economies in six categories: financial system development, modern innovation system, market competition, trade openness, direct investment openness, and portfolio investment openness. The first three clusters represent the “domestic” dimension, and the latter three clusters represent the “external” openness dimension.

We rely on Annual Indicators that are formed into a composite score each year. Each of the six categories outlined above possesses a set of annual indicators and a final composite index. In addition, we select nuanced supplemental indicators and conduct quarterly policy tracking to keep up with fast-moving economic and policy developments in China.

This year’s China Pathfinder measures the 2020 performance of eleven countries—and China’s 2010 performance—in the same standardized metrics. The selected country list is as follows: Australia, Canada, China, France, Germany, Italy, Japan, South Korea, Spain, the United Kingdom, and the United States. Aside from China, all other countries are members of the Organisation for Economic Co-operation and Development (OECD) and are considered market economies. These specific countries were chosen according to being in the top-ten country list for highest gross domestic product (GDP).

China Pathfinder added China’s 2010 performance as a datapoint to benchmark China’s present-day progress since the last decade. That also provides data prior to the start of President Xi Jinping’s administration and can provide an objective picture of how China’s economy has developed since.

Annual Indicators

Our criteria for selecting annual indicators has two main components: data timeliness and ability to make international comparisons. These criteria inherently limit each other, as timely data often do not have extensive country coverage. This created obstacles in our data collection process, and the path we chose with our annual indicators reflects the ideal solution to these data availability problems.

The annual China Pathfinder report has a foundation of quantitative methods and sources. It mixes source types for data analysis. We make use of existing credible databases and literature, such as the OECD, International Monetary Fund (IMF), and World Bank datasets and indices; platforms such as CEIC and Bloomberg for China-specific statistics and company financial data; and expert buy-in for our in-house production of proprietary datasets.

Along with compiling research from these data sources, China Pathfinder also incorporates indicators that were informed by study groups and expert interviews. Our team conducted review sessions with various outside experts on China and OECD economies, index creation, and construction of cross-country economic evaluations. We have implemented feedback and new ideas gathered from these conversations to improve our annual indicator selection.

Composite Scoring

A composite indicator employs a defined model for selecting a group of individual indicators and transforming them into a single index. Composite indicators are common tools in policy analysis, particularly for maintaining objectivity in comparing country performance. The China Pathfinder takes guidance from the OECD Handbook on Constructing Composite Indicators: Methodology and User Guide, which compiles various statistically sound methodologies for economists and policymakers to build composite indicators.

To calculate composite scores, we use the Min-Max methodology. This is necessary to normalize countries’ scores from the individual indicators, which have different units and scales. The Min-Max normalization method was selected because it preserves country clustering and countries’ relative performance distance. Min-Max uses each dataset’s minimum and maximum datapoints to establish a “lower bound” and “upper bound.” Each country value X within a given indicator is taken in relation to these bounds. China Pathfinder subtracts the lower bound from the country value and then divides the outcome by the difference in the upper and lower bounds. This normalizes every indicator from zero to one. We use a scale of 0–10 for the composite scores, so the datapoints are multiplied by ten after completing the Min-Max process.

Some indicators have opposite implications for large values and small values. For our purposes, we set the following standard for all indicators and composite score readings: smaller values (i.e., those closer to zero) indicate “low” and larger values (i.e., those closer to ten) indicate “high” openness or development. Some indices that we adopt measure restrictiveness levels on foreign direct investment (FDI) or capital flows, and larger values represent greater restrictions on openness. For indicators that follow this pattern, we reversed the values before initiating the Min-Max method for the composite. Value reversal involved setting the maximum bound for these indicators and using it to subtract each country datapoint.

China Pathfinder’s composite indices blend de jure and de facto indicators. De jure indicators measure a country’s institutions or legal framework characteristics, while de facto indicators are outcome oriented and seek to measure the actual effects of said institutions. While there is an argument to be made for using one or the other, we chose to integrate both into a blended composite score for each cluster. Selecting only de jure indicators opens the possibility that policies or institutions in place do not necessarily evenly result in the same expected outcomes, or reflect the true situation for some countries. Using de facto indicators solely is particularly challenging with external factors, such as the COVID-19 pandemic, that greatly skew real outcomes temporarily. This approach also fails to afford credit to countries that have implemented institutional reforms, when resulting progress has a lag.

We assign equal weighting to de jure and de facto indicators in the composite index calculation when the indicators have comparable importance to defining our cluster evaluation. Otherwise, each individual indicator receives the same weight regardless of de jure or de facto designation.

Supplemental Indicators

Chosen indicators within each area are intended to proxy for the broader picture, but do not encompass all aspects of an economy. Therefore, narrower factors that affect China’s performance evaluation are featured as “supplemental indicators.” Supplemental indicator data outcomes receive their own chart visualizations, but the data generally cannot be applied to all countries in our sample. For example, some poignant indicators lack data coverage for many countries in our sample, besides China. This complexifies our process for comparing China with the top open market economies on the same standards. For this reason, supplemental indicator data do not contribute to a country’s final composite score.

Numerous data-compilation methods are used in building our supplemental indicators. Some indicators are reflections of standard metrics, and others are modified in house to illuminate certain aspects of metrics that already exist. Finally, China Pathfinder applies a handful of existing proprietary indicators developed by Rhodium Group.

Policy Tracking

China Pathfinder supplements its yearly quantitative assessment with quarterly policy tracking. After compiling all relevant major policy developments in China during a specific quarter for each of our six clusters, we systematically evaluate each development. The evaluation process contains four possible signals for China’s policy momentum: movement toward, movement away, mixed movement, or no change in relation to open-economy standards. After aggregating all positive, negative, mixed, and stagnant developments in China’s policy atmosphere, China Pathfinder presents a heatmap within its quarterly report showing the outcome.

In examining policy changes, our team specifically looks for policies that connect back to the benchmark signals that we outlined in Section 2’s “Looking Forward: Market-Oriented Policy and Data Signals.” This provides some continuity between our annual report’s quantitative-driven outcomes and the policy considerations elaborated upon in quarterly reports.

Applications and Caveats

While China Pathfinder is intended to be a quantitative resource for policymakers, economists, and business leaders to benchmark the Chinese economy and stay informed about China’s policy developments, it is not a comprehensive assessment of every aspect of China’s economy. Our research design is deliberately narrow, focusing on just enough to permit a clear picture of China’s compatibility with market economies without hindering reader accessibility.

The choice to track China’s system vs. open market economies, rather than a broader set of emerging and developing economies, was a deliberate one. We fully acknowledge that China does not have any intention to become a democratic open market economy. However, we postulate that OECD policymakers can only maintain open and engaging economic policies with China if there is movement in a similar direction.

Our project concept opens the question of whether China should be expected to converge with advanced OECD nations, instead of the opposite. Aiming for fairness in the China Pathfinder evaluation, we compare China not on areas in which our sample of market economies are already structurally perfect, but on agreed-upon norms integral to an open economic system.

Research Dissemination and Data Visualization

The China Pathfinder project provides visualizations for indicators in six areas that will be updated with new data annually. It preserves 2010 as a benchmark year for China’s performance, a data point that will live through future iterations of composite scoring and individual indicator analysis.

To add nuance and include higher frequency data on the Chinese economy, supplemental indicators are refreshed on a quarterly basis. In the face of unexpected large-scale developments, the supplemental indicator list will expand or be modified to ensure maximum utility for the user.

Data visualizations are created by Seven Mile Media, and range from interactive data features on the website and graphical representations throughout annual and quarterly reports.