Dirk Willem te Velde (Principal Research Fellow, ODI)
18 May 2020
A multitude of trackers cover policy responses to COVID-19 but when it comes to up-to-date monitoring of actual social and economic impacts there appears to be a gap. Impact data are not collected systematically and in a comprehensive manner. Obtaining access to reliable, good quality statistical data for the poorest countries is a challenge; it is even more difficult to monitor economic data in real time or at high frequency and with a short time lag.
ODI has monitored a range of macroeconomic crises (e.g. the global financial crisis, the Eurozone crisis and crises related to oil prices and food price hikes) using economic data. This work provides lessons with regard to what high frequency data can be used to monitor the impacts of COVID-19 globally, and specifically those on the poorest countries.
The table below presents data sources in the following areas:
- Commodity prices, food prices and hunger;
- Global and bilateral trade, trade costs and mobility;
- Capital markets, finance flows and fiscal and monetary statistics; and
- Employment and production.
High frequency data are published daily, weekly, monthly or quarterly. Some are available immediately; some come with a time lag of a few days or weeks; yet others take several months to become available. Some data include noise (rather than signal) and much variability; others are cleaned, adjusted for variability or more robust. Some data are publicly available (we focus mostly on these); others are available behind a paywall.
So far, data for commodity and food prices appear to be covered well, perhaps in part because the G20 has paid attention to monitoring these for several years. Trade data are also available but with a time lag. Data on capital markets and finance flows are available but patchy, and often behind paywalls for use by investors. High frequency data on employment and production tend to be weakest: they are not available for a few months and there are well-known challenges with such data.
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Commodity prices, food prices and hunger
| Source and frequency | Comments on use | Hyperlinks and examples | |
| Commodity prices (global prices) | Available immediately (e.g. FT for oil/copper prices; IMF/WB weekly/monthly averages with a short time lag (a few weeks) | Variable reflecting many issues such as supply/demand and others | Oil price (paywall) IMF World Bank Price data (pink sheet) GroAgro |
| Food prices (domestic prices) | FAO food prices, monthly (a week time lag) IFPRI’s Food Price Monitor covers daily price data for domestic markets in India, Rwanda, Uganda and Burundi National statistics offices | Localised data patchy | FAO food price index IFPRI dashboard |
| Hunger | WFP, number of people with insufficient food consumption, countries with very high levels of hunger, updated daily and weekly | Limited countries now (9 African now) but 16 more planned in coming weeks; it is a forecast. Weekly snapshots for 14 countries | WFP Food Hunger Map WFP daily report Weekly snapshots |
| COVID cases, deaths | Daily across countries | Available widely, commonly used sources but difficult to compare across countries | Johns Hopkins |
| High frequency telephone interviews around social and food security impacts | Monthly updates from May 2020. Cover topics including (i) knowledge of existence of and channels of transmission of COVID-19; (ii) knowledge of and compliance with preventive measures with specific emphasis on social distancing and self-isolation; (iii) prices and access to food and non-food necessities; (iv) employment; (v) food insecurity; and (6) subjective well-being – with a focus on understanding the dynamics of economic impacts | Once available will be very valuable, for Ethiopia, Malawi, Nigeria, Tanzania, Uganda | LSMS high frequency phone surveys, |
Global and bilateral trade, trade costs and mobility
| Source and frequency | Comments on use | Hyperlinks and examples | |
| Trade costs | Baltic Exchange Dry Index Trading Economics, daily | Specific cost measure, does not cover many transport uses/modes | Trading Economics |
| World trade | CPB world trade indicator, monthly, available with a one- to two-month time lag IMF tracking of world trade using real-time shipping data | Partly a leading indicator, partly real data Uses data for dry bulk, contain, vehicle, oil shipping data | CPB indicator described in FT IMF tracker |
| Bilateral trade | National statistics office and ITC trade map (monthly data for major countries such as UK, EU, US, China and Japan available with a six-week time lag; annual data for low-income country source) International data reported monthly with time lag (UN Comtrade) | Trade data variable but long-runs are available | UK monthly trade stats German monthly data Comtrade |
| Mobility and entertainment | Aircraft departures, bus and rail journeys; Google searches for entertainment, seated diners, retail footfall (updated daily) Google Mobility data for retail, grocery, parks, transit, workplaces, residential visits (weekly) | Not easily available beyond reports Google data for all countries on a weekly basis | Bank of England Monetary Policy Report Chart 2.26 COVID-19 Community Mobility Reports |
Capital markets, finance flows and monetary statistics
| Source and frequency | Comments on use | Hyperlinks and examples | |
| Remittances | Central banks, monthly data, available with one to three months time lag | Can vary much between months | Nigeria Kenya |
| Stock market prices, exchange rates, bond yields | Available daily and immediately, e.g. FT or central bank Bond prices and bond spreads (yield difference countries and safe havens such as US/German bonds) | Varied sources but often subscription is needed FT/Bloomberg often report statistics/figures | FT (paywall) |
| Private capital flows to emerging markets | IIF monthly updates on portfolio flow but not FDI flows, available with one to two years of lag (committed FDI data more recent) | Lacks country details | IIF |
| Bank lending statistics | BIF international bank lending, quarterly, available with five-month time lag | BIS | |
| Monetary statistics (central bank) | Central banks maintain monthly and quarterly data on the monetary base and broad money, credit aggregates (e.g. to the private sector) and foreign assets and liabilities. Includes claims by banks on government | Quality data on a select number of variables | Kenya |
| Debt interest payments | Monthly/quarterly, central bank websites, lags can be six months | Kenya (Table 13) Nigeria debt service in 2019 Ethiopia | |
| Aid flows | OECD DAC Humanitarian finance: COVID-19 Global Humanitarian Response Plan | DAC (and national) data are available with long time gaps (a year) but humanitarian finance data are updated weekly; announcements are available | OCHA ODI donor announcement tracker |
Employment and production
| Source and frequency | Comments on use | Hyperlinks and examples | |
| Employment | ILOSTAT provides monthly and quarterly labour force statistics (with a time lag of at least two months) | Up-to-date data are patchy with respect to country coverage | ILO COVID-19 and labour market statistics |
| Production | National accounts, quarterly, available with six-week time lag in developed countries, or a lag of three to five months in some poorer countries UNIDO has recent data on industrial production, e.g. for the US, China, Russia, Korea, Vietnam, Argentina, Chile, Poland | Data available with long time lag, and industrial production data cover few countries | UNIDO on impact of COVID-19 on manufacturing |
Others (selected)
| Source and frequency | Comments on use | Hyperlinks and examples | |
| Data Portals | World Bank, updated in an ongoing manner Several others exist ODI’s tracker of trackers (tba) | Datasets from the World Bank World Bank: COVID and trade UN Global Partnership for Sustainable Development Data |
Photo: Changes in food prices as a result of Covid-19. John Mackedon / World Bank . CC BY-NC-ND 2.0