Emerging Markets Review

We estimated all the results in the paper using the R software. Related codes, along with the sample data, are all in the compressed file. There are four data files: 1. “Exchange.csv” is the monthly exchange rate series used for most empirical analyses. 2. “Exchangeewma.csv” is the daily exchange rate for later robustness checks. 3. “Table.csv” is the sample used for later further investigation. 4. “Swap.xlsx” is the handy-collected data about the detailed information of bilateral currency swap arrangements between the People’s Bank of China (China’s central bank) and central banks of other countries (or regions). Table A1 in the appendix of the paper summarizes this detailed information.

This dataset collects data on China's A-share listed companies in 2018 and 2019. Symbol Meaning Calculation formula Stkcd Stock code -- CSRPI corporate social responsibility participation index a weighted average of criteria and weights EVAr relative EVA the ratio of EVA to total capital MA company mature stage Dummy variable：for a mature company 1, otherwise 0. SIZE company size the natural log of total assets of a company LEV financial leverage the ratio of total debt to total assets EOC equity ownership concentration the ratio of the largest shareholder ownership（%） CH cash holding rate the ratio is the sum of cash balance and marketable securities divided by total assets R&D R&D expense rate the ratio of R&D expense to total assets AGE company age indicator the natural logarithm of company age Industry the company's industry categorical variable with two-digit codes for each industry Year years of analysis the 2018 sample is 2018, and the 2019 sample is 2019 ROE Return on Equity the ratio of net profit to equity CSRPIe corporate social responsibility participation index a simple average with equal weight for each criterion Mature5 company mature stage Dummy variable：for a mature company 1, otherwise 0.

This dataset is used to perform a systematic literature review and a bibliometric network analysis of studies on African financial markets from 1992 to 2021. We began by identifying the appropriate string of keywords. We identified and agreed to use the following keywords string for the search: “African market”, African stock markets”, African equity markets”, “African capital market”, “African financial market”, “African foreign exchange market”, “African exchange market”, “common stocks” and “African”. These keywords were searched in the Title, Abstract or Keywords (TAK) functionality of Scopus and they resulted in 321 hits as of March 10, 2022. We then apply two main quality thresholds, namely, subject area and language restrictions. We restricted the subject area to “Economics and Finance”, while we set the language to “English”. As we are interested in knowing the trajectory of the 30-year literature on African financial markets, we set limit on the “end date” to 2021 as well as “document type” to journal articles. These restrictions resulted in 198 relevant articles for download for the bibliometric analysis.

This database is for Political Connections, Political Cycles and Abnormal Returns: Evidence from Iran.

Estimated MPU and data for subsequent VAR analysis

China's monetary policy uncertainty

Two datasets covering the abnormal returns of bank acquisitions on the African continent over the period 2000-2017. Control variables include bank level data from SNL, macro-economic and institutional data from the worldbank and deal level data from SDC platinum.

This dataset includes the stock prices of 45 Chinese financial institutions and the Fama and French (1993)'s three factors in Chinese stock market. The stock prices of 45 institutions are obtained from the Wind dataset, while the three factors are gained from the CSMAR dataset. The time span of these data is from December 31st, 2004, to November 30, 2016.

The file contains the returns on asset pricing factors used in the study.

The series are: CO2 emissions, energy consumption, GDP, industry value added, agriculture value added, FDI and urban population.