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International Monetary Fund. Statistics Dept.
In response to a request from the authorities and as part of the Data for Decisions (D4D)1 funded project under the submodule for Fiscal and Debt reporting, a government finance statistics (GFS) technical assistance (TA) mission was held remotely with the Lesotho Ministry of Finance (MOF) during April 5–16, 2021. Previous TA missions under the Enhanced Data Dissemination Initiative (EDDI2) over the period spanning from 2016 to 2020 assisted the MOF to improve GFS compilation and dissemination for the budgetary central government (BCG) and inspired action to broaden data coverage to include local governments and extrabudgetary units (EBUs) with the aim to compile and disseminate consolidated general government GFS. Preliminary local government GFS have now been compiled, and data collected for selected state-owned enterprises (SOEs) and parastatals, including non-market SOEs that can now contribute to preliminary general government GFS to be compiled.
Ms. Li L Ong, Mr. Phakawa Jeasakul, and Miss Sarah Kwoh

. Data and Methodology Banks’ financial statements data (preferably audited) are required for calculating the BHI. For the purposes of this paper and the application of the enclosed HEAT! template, data from the BankScope, Bloomberg and SNL databases are used. As a rough and ready measure of individual banks’ health, we calculate simple CAMELS 2 -type ratings for each institution in the defined sample. A BHI is subsequently derived from the ratings and a heatmap is generated to provide a snapshot of a particular bank or banking system. A description of the method