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'Social capital, income inequality and COVID-19 mortality'

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1) Have any data been collected for this study already?
It's complicated. We have already collected some data but explain in Question 8 why readers may consider this a valid pre-registration nevertheless.

2) What's the main question being asked or hypothesis being tested in this study?
We are investigating the idea that country-level social capital and income inequality will be predictive of country-level prevalence of COVID-19 and mortality due to COVID-19. We intend to test two hypotheses:

H1: Using country-level data on social capital and public data on COVID-19 deaths during the 30 days after 10 confirmed deaths, we expect to find negative associations between social capital and mortality (after controlling for population, wealth, and income inequality).

H2: There will also be a positive association between income inequality and COVID-19 mortality.

3) Describe the key dependent variable(s) specifying how they will be measured.
The key dependent variables are as follows.

Main dependent variable:
Daily data on COVID-19 deaths, by country – provided by the European Centre for Disease Prevention and Control

Main independent variables:
(1) Trust, Groups, Civic and Linking Social Capital – measured by the World Values Survey Social Capital Index (Elgar et al., 2011) using data from cycles 5 and 6 of the World Values Survey.
(2) Income inequality (measured by the Standardized World Income inequality Database (Solt, 2019)

Main control variables:
(1) Per capita income – International dollars, Atlas method, provided by the World Bank Database;
(2) Country population – published by the UN Population Division;
(3) Testing prevalence – based on “Our World in Data”, reported as the number pf tests per million of inhabitants in a country.


4) How many and which conditions will participants be assigned to?
There are no conditions in the proposed analyses.

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Multiple linear regression with panel-corrected standard errors (xtpcse in Stata 16.1) on log-transformed deaths during a 30-day time period. Country panel data will be anchored on the date the country recorded is 10th COVID-19 death. We will exclude countries that have not recorded at least 10 deaths as of April 10, 2020.

6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
Outliers on any variable (>3 SDs from the mean) will be excluded.

7) How many observations will be collected or what will determine sample size?

The sample will include at least 48 countries and 656 day/country observations.

8) Anything else you would like to pre-register?

We are pre-registering an existing data analysis. No new observations will be collected as all the analyses will be conducted using existing data.

We are also going to examine the number of cases infected with COVID-19 as a dependent variable. However, because infection rates are the product of testing (and people seeking tests) this data is expected to be much less precise. All things being equal, we expect the results for “number infected” to mimic the results for “number of deaths due to COVID-19”. However, due to the noise in the “infected data” we are reluctant to make an unequivocal hypothesis.