Note: The Index was previously called the FRT and is still referred to as such throughout much of the replication material.
Maintainer: Christopher Gandrud
Funding generously provided by the Deutsche Forschungsgemeinschaft (Grant No. HA5996/2-1).
Work In Progress
Why do countries release data on their financial systems to international organizations, such as the IMF and World Bank? What are the consequences of releasing this data for the stability of their financial systems?
To address these questions we are developed a Financial Data Transparency Index. The new Index we make it possible to compare the willingness of governments to credibly reveal the structure of their financial systems through international institutions, allowing them to be scrutinized by market participants and citizens.
We presented an early draft of a research using the FDT at the 2015 Political Economy of International Organizations conference. The working paper can be found here.
The current draft version of the Index is located in the IndexData directory in a CSV formatted file called: FRTIndex.csv.
It covers the 68 countries classified by the World Bank as 'High Income', EMBI countries, China, and India for the years 1990 through 2011.
The file FRTIndex.csv
contains the following variables:
Variable Name | Short Description |
---|---|
country | country name |
iso2c | ISO 2 letter country code |
year | year of the FDT score |
lower_95 | lower bound of the 95% highest probability density interval |
lower_90 | lower bound of the 90% highest probability density interval |
median | median of the FDT index posterior distribution |
upper_90 | upper bound of the 90% highest probability density interval |
upper_95 | upper bound of the 95% highest probability density interval |
se | standard error of the posterior distribution |
To download the working version of the Index directly into R as a data frame use:
URL <- 'https://raw.githubusercontent.com/FGCH/FRTIndex/master/IndexData/FRTIndex_v2.csv'
frt_index <- rio::import(URL)
The FDT Index is created using a Bayesian Item Response Theory model of high income countries's reporting of financial industry indicators to the World Bank's Global Financial Development Database.
A full write up of our model is in the works. The most recent (incomplete) draft is available for download as a PDF.
Our estimation model is based on:
Hollyer, James R., B. Peter Rosendorff, and James Raymond Vreeland. 2014. "Replication data for: Measuring Transparency". http://dx.doi.org/10.7910/DVN/24274
and
Stan Modeling Language: User's Guide and Reference Manual for Stan Version 2.5.0. p. 49-59.
We have built on this model using the No-U-Turn Sampler implemented in Stan.