Nobel Prize & Chinese Economists' Research
Description
Data Description for Online Repository (Multiple Excel Sheets) This dataset supports the analysis in “Chinese Economists and the Nobel Prize Dilemma: Cultural Bias or Paradigmatic Misalignment Between Theory and Application.” It consists of bibliometric and coded variables from 2,604 research articles published in Economic Research Journal (2000–2019). The dataset is structured across multiple Excel sheets to allow clarity and reproducibility. Contents by Sheet: Metadata – Publication year, author names, institutional affiliations, keywords, and abstracts. Research Questions (NQ) – Coding of theoretical (Nobel Query, “why”) vs. applied (“how”) research orientations, with additional categories (where, when, whether, method). Contextual Levels (NC) – Indicators of scope: individual, firm, industry, national, and international contexts. Temporal Indicators (NT) – Publication year, pre-/post-2008 financial crisis, pre-/post-2013 Belt and Road Initiative. Disciplines – Article classification into subfields (e.g., macroeconomics, microeconomics, econometrics, financial economics, institutional economics). Regression Variables – Cleaned binary and categorical variables used for multivariate and logit regression analyses (including dependent and independent variables). Codebook – Definitions of all variables, coding rules, and examples of applied vs. theoretical classification. File Format: Provided as an Excel workbook (.xlsx) with seven sheets. Variable names and coding notes are harmonized for ease of replication and further analysis. Usage: The dataset enables replication of descriptive statistics, regression analyses, and figures reported in the article, and serves as a resource for future research on applied versus theoretical orientations in Chinese economics.
Files
Steps to reproduce
Steps to Reproduce Download the Dataset Obtain the Excel workbook provided in the online repository. The workbook contains seven sheets: Metadata, Research Questions (NQ), Contextual Levels (NC), Temporal Indicators (NT), Disciplines, Regression Variables, and Codebook. Review the Codebook Begin with the Codebook sheet to understand variable definitions, coding categories, and examples (e.g., why vs. how questions, national vs. international context). Prepare the Data Import the Excel file into your statistical software (Stata, R, Python, or SPSS). Ensure variable types are correctly recognized (binary, categorical, string, or numeric). Replicate Descriptive Statistics Generate summary statistics of research question types, contextual levels, and temporal indicators. Reproduce frequency tables and cross-tabulations as reported in the article. Replicate Figures Use the coded variables to reproduce coefficient plots, contextual preference charts, and time-trend figures (2000–2019, pre-/post-2008 crisis, pre-/post-2013 BRI). Run Regression Models Apply logit regression models (for Nobel Query classification) and multivariate regression models (for alignment with contexts and temporal indicators). Use the regression variables sheet for dependent and independent variables, controlling for discipline and context. Compare Results Match regression outputs (odds ratios, coefficients) with Tables 1–9 in the article. Validate graphical outputs against Figures 2–6. Extend Analysis (Optional) Researchers may expand the dataset by integrating additional journals or post-2019 publications, applying the same coding scheme for comparability.
Institutions
- Liaoning University