Global Policy Tracker
By: Alberto Cavallo and 25 MBA/Harvard students
[Note: the Global Policy Tracker is no longer active. We collected data of the initial policy response in over 50 countries from March to May 2020. The database will remain online and we hope it is useful to anyone who wishes to understand how the initial policy responses compared across countries.]
The HBS Global Policy Tracker is an initiative to collect and standarize economic policies implemented as a response to the Covid-19 pandemic around the world. We focus on fiscal policy, monetary policy, and lockdowns. The data is updated in real-time with the efforts of several dozens of students and staff at HBS and other Harvard Schools.
A key characteristic of this tracker is that we try to quantify government responses in common variables, units and currencies to facilitate cross-country comparisons and outcome evaluation over the course of the spread of the pandemic. Download the working paper with more details about the data collection and data processing methodologies.
If you are interested in submitting ongoing policy changes in your country to add to our database, you can fill out the form here.
Please read the COVID-19 Business Impact Center Terms of Use
Policy Database
Download the policy database in Excel format. This file is automatically processed and cleaned several times during the day.
Summary Statistics by County
This cross-country summary table facilitates cross-country comparisons We include aggregate totals and binary indicators by policy types and subtypes.
Type of Policies Tracked
The HBS Global Policy Tracker uses publicly available media and government sources to identify new and changing government policies. We divide policies into fiscal, monetary, and lockdown types. Each policy is also categorized into subtypes, as listed below.
Type | Subtypes | Description & Examples |
---|---|---|
Fiscal | General | Total amount of the announcement. Used only when the policy is not divided into other subtypes. |
Direct Spending | Infrastructure, hospitals, public transit, etc. The government is buying the goods or services. | |
Direct Transfers | Transfers for poor families, UE insurance payments, grants for businesses (no repayment), aid to states (not loans). Not that the government is not doing the actual spending in these cases. | |
Tax Benefits and Cuts | Tax cuts for people or business, extending deadlines or adding exceptions. | |
Loans | When repayment is expected (not a grant). To people, businesses, provinces, any other. | |
Regulation | More flexible/simpler regulations, reducing firms' costs that are not taxes. | |
Other | Used when we are splitting the policy amounts in subtypes and we cannot classify part of the policy into the other subtypes. Only the partial amount that could be not classified is included here. | |
Lockdown | Partial | Partial if it does not cover the whole country or lockdown not complete or loosely enforced. |
Full | Cases with exceptions for "essential businesses", or such should be considered Full. Use your judgement here to decide. | |
Monetary | Rate cuts | Traditional policy rate cuts (fed funds rate, discount rate, etc.) |
Lending to Government | CB directly buys government bonds (or other form of lending) from the central government. | |
Change in Reserve Requirement | Change in bank's required reserve ratios. | |
Credit Facilities to Financial Institutions | CB is lending to commercial and non-commercial banking institutions (eg. investment banks, money market funds). | |
Credit Facilities to Corporations | CB is lending to non-financial institutions (ie. buying corporate bonds directly from firms). | |
QE (large scale asset purchases) | CB is buying large/unlimited quantities of non-traditional assets (long-term gov bonds, corporate, etc.). | |
Exchange Rate or Capital Controls | Government limits access to the foreign exchange market or restricts money otherwise coming in and out of the country. | |
Other | Undefined. | |
Other | To be classified/standardized later. |
Collected Variables
The variables collected by our team are shown in Table 1. We include the date of the announcement, the type and subtype of the policy, and the start and end dates of the policy. The nominal amount of the policy is entered in the original currency and units announced.
Variable | Explanation |
---|---|
Date of Announcement | The date of the policy announcement. We use an approximate date if the details are not available. |
Reference | The url to the information source. Can be a primary source (government announcement) or a newspaper article from a reputable media outlet. |
Type of Policy | Drop-down list of from the previous table. |
Subtype | Drop-down list of from the previous table. |
Policy Description | Open text field. Add a brief description of the policy. Anything considered relevant/useful to know. |
Amount | Only numbers (no $ signs). |
Currency | LCU (local currency unit) or USD, as reported in the reference source. |
Unit | Trillions, Billions, Millions, or thousands, as reported in the reference source. |
Start Date | When the policy is supposed to start. |
End Date | When the policy is expected to end (if announced). Blank if unknown. |
Calculated Variables
To facilitate international comparisons of the policies announced, we re-express all nominal values in millions of LCU, millions of USD, and as a percentage of GDP in 2018 (the last available year for most countries).
Variable | Explanation |
---|---|
Amount_Millions_LCU | We use the Unit variable to re-express the amount in millions. If the announcement was made in USD, we divide it by the Nominal Exchange Rate (defined as USD per unit of LCU). |
Amount_Mllions_USD | We use the Unit variable to re-express the amount in millions. If the announcement was made in LCU, we multiply it by the Nominal Exchange Rate (defined as USD per unit of LCU). |
Percent_GDP_2028 | We divide Amount_Millions_USD / Milion of USD GDP 2018. |
The GDP in current USD for 2018 is sourced from the World Bank. Exchange rates are obtained from the Alpha Vantage Stock API, a company created by Steve Zheng (HBS '18) and Olivier Porte (HBS' 18). For spreadsheet access to the stock API domain, you may refer to the Google Sheet Add-on and Microsoft Excel Add-on of Alpha Vantage.
Team
Team Lead: Alberto Cavallo (Associate Professor HBS - BGIE group)
HBS Students: Tannya Cai (project manager), Alex DeVille, Angel Rodriguez, Anna Sakellariadis, Bhumika Agarwalla, Camille Gregory, Dvij Bajpai, Enrique Elias, Eufern Pan, Joaquin de la Maza, John Guo, Joyce Zhang, Lau Skovgaard, Marcia Ambrosi, Margherita Pignatelli, Ratnika Prasad, Rei Morimoto, Rohan Vora, Roni Luo, Ruth van Montfort, Ryan Yu, Soichiro Chiba, Sophia Lien, Ukasha Iqbal, Umang Sota.
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Tannya Cai (PM) HBS MBA ‘21 |
Bhumika Agarwalla HBS MBA ‘20 |
Ratnika Prasad HBS MBA '20-MPA/ID |
Roni Luo HBS MBA '20 |
Ruth van Montfort HBS MBA ‘21 |
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Umang Sota HBS MBA ‘21 |
Margherita Pignatelli HBS MBA '20 |
Soichiro Chiba HBS MBA ‘21 |
Joaquin de la Maza HBS MBA ‘20 |
Sophia Lien HBS MBA ‘21 |
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Eufern Pan HBS MBA ‘21 |
Alex DeVille HKS MPA-ID '21 |
Anna Sakellariadis HBS MBA ‘20 |
Angel Rodriguez HSPH PhD |
Dvij Bajpai HBS MBA ‘21 |
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Camille Gregory HKS/HBS MBA ‘21 |
Enrique Elias HBS MBA ‘20 |
Joyce Zhang HBS MBA ‘21 |
John Guo HBS MBA ‘20 |
Lau Skovgaard HBS MBA ‘21 |
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Marcia Ambrosi HBS MBA ‘21 |
Ryan Yu HBS MBA ‘21 |
Rei Morimoto HBS MBA ‘21 |
Rohan Vora HBS MBA ‘20 |
Ukasha Iqbal HBS MBA ‘21 |