Wilson Asiimwe
Norwegian University of Life Sciences, Economics and Resource Management, Alumni https://www.nmbu.no/en
I am a Senior Economic Modeller at the Ministry of Finance, Planning and Economic Development Uganda, in the Macroeconomic Policy Department. Am also a MEFMI Graduate Fellow. My expertise is in Macroeconomic Modelling and Forecasting especially in Computable General Equilibrium (CGE) Modeling.
I have hands-on-experience in building economic models. At the Ministry of Finance Uganda, I co-led the team that constructed the Uganda Integrated Macroeconomic Model (IMEM) and as a result, in FY 2016/17 I received the performance award for being the best technical staff in Macroeconomic Policy Department for the year. My roles at the Ministry of Finance include; Macroeconomic Modelling and Forecasting, Fiscal and Monetary policy analysis, Oil and Gas sector analysis, coordination of Social Accounting Matrix (SAM) construction as well as coordinating macroeconomic policy research. The tools I use include; Macro-econometric models (using Eviews), Micro-simulation models (using Stata), Computable General Equilibrium (CGE) Models (using GAMS/GEMPACK) and Dynamic Stochastic General Equilibrium (DSGE) Models (using Matlab). I also use ISIM-MAMS model and Gempack software for Dynamic CGE Models. In addition to my experience at the Ministry of Finance, Uganda; I lectured Natural Resource Economics at Kyambogo University in Uganda for a period of 2 years and currently I have an additional role of training government economists in Uganda on how to use the Integrated Macroeconomic Model (IMEM).
I holds a Bachelor of Arts in Economics degree from Makerere University (Uganda), and an Msc in Development and Natural Resource Economics from Norwegian University of Life Sciences, Norway. I also hold a Masters in Financial Engineering from WorldQuant University, USA.
www.linkedin.com/in/wilson-asiimwe-744246a0
https://www.finance.go.ug/
https://www.nmbu.no/en
https://www.mak.ac.ug/
https://macrosolve.net/
Supervisors: Dr. Albert Musisi, Commissioner Macroeconomic Policy Department - MOFPED
Address: Plot 37, Acacia Avenue, Kololo, P.O.Box 9242 Kampala, Uganda
I have hands-on-experience in building economic models. At the Ministry of Finance Uganda, I co-led the team that constructed the Uganda Integrated Macroeconomic Model (IMEM) and as a result, in FY 2016/17 I received the performance award for being the best technical staff in Macroeconomic Policy Department for the year. My roles at the Ministry of Finance include; Macroeconomic Modelling and Forecasting, Fiscal and Monetary policy analysis, Oil and Gas sector analysis, coordination of Social Accounting Matrix (SAM) construction as well as coordinating macroeconomic policy research. The tools I use include; Macro-econometric models (using Eviews), Micro-simulation models (using Stata), Computable General Equilibrium (CGE) Models (using GAMS/GEMPACK) and Dynamic Stochastic General Equilibrium (DSGE) Models (using Matlab). I also use ISIM-MAMS model and Gempack software for Dynamic CGE Models. In addition to my experience at the Ministry of Finance, Uganda; I lectured Natural Resource Economics at Kyambogo University in Uganda for a period of 2 years and currently I have an additional role of training government economists in Uganda on how to use the Integrated Macroeconomic Model (IMEM).
I holds a Bachelor of Arts in Economics degree from Makerere University (Uganda), and an Msc in Development and Natural Resource Economics from Norwegian University of Life Sciences, Norway. I also hold a Masters in Financial Engineering from WorldQuant University, USA.
www.linkedin.com/in/wilson-asiimwe-744246a0
https://www.finance.go.ug/
https://www.nmbu.no/en
https://www.mak.ac.ug/
https://macrosolve.net/
Supervisors: Dr. Albert Musisi, Commissioner Macroeconomic Policy Department - MOFPED
Address: Plot 37, Acacia Avenue, Kololo, P.O.Box 9242 Kampala, Uganda
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shifting a quarter of the aid funds to the local actors, performance has remained low. By 2021 less than one percent of the humanitarian aid was being allocated to local actors. Though recent scholars have postulated that redirecting aid funds to local actors might be beneficial, there is limited quantitative literature to support this proposal, especially for the case of Uganda. Based on this background, this paper uses a Dynamic Computable General Equilibrium model to assess the macroeconomic impacts of shifting aid funds from traditional spending architecture to direct cash transfers for households in Uganda.
The findings reveal that shifting aid funds to local actors (households) provides macroeconomic benefits to the economy and generates spillover effects to non-recipient households and other economic agents. Financing the cash transfers by reducing allocations to government and so-called ‘Non-Profit Institutions Service Households’ increases tax revenues, household incomes and savings. However, employment and economic growth decline as the actual appreciation of the exchange rate reduces international competitiveness. The decline in economic growth is driven by a decline in industry and service sector GDP as agricultural GDP increases. The alternative scenario of financing social cash transfers by reducing the overheads of offshore aid is the most effective in improving economic growth, household incomes, government tax returns, employment and household savings and investment. International humanitarian donors and aid organisations are urged to consider re-directing aid funds from the overseas overhead costs to local actors through direct SCT to vulnerable households. This will improve household welfare, investment and employment and accelerate economic growth.
crisis are severe, erasing poverty gains of the past 10 years, and reaching well beyond Kampala. Using household-level information from the 2016/17 Uganda National Household survey, we explore four different transfer schemes that the government might use to offset the poverty consequences of the crisis: (i) a universal transfer to all households based on their adult equivalence size, but excluding households with income from employment in the public sector or a public sector pension; (ii) a transfer of the same size as in (i), but targeted to only those households that were poor before the crisis began; (iii) an expansion of the SAGE grant to all those 65 years old and older; and (iv) a labor-intensive public works program directed at the hardest hit
urban areas.
This paper and accompanying excel workbook describe the construction of a SAM for Uganda for the 2016/17 financial year. We discuss the structure of the SAM as the various sources of data. The data sources
include the Supply Use Table for 2016/17, Government Financial Statistics (GFS), Ugandan National Household Survey, Balance of Payments and financial data. The development of the SAM is completed in 2 steps. First a Macro SAM is developed. This Macro SAM is then disaggregated further by disaggregating the activities and commodities accounts, labour income and expenditure, and the household accounts.
We do not present the Full SUT and SAM as part of this paper. To access the Full SUT, contact the Ugandan Bureau of Statistics (UBOS)1, and to access the Full SAM, contact the Ministry of Finance, Planning and Economic Development (MoFPED).
and output to strengthen effectiveness of monetary policy.
double the returns to labor. These results are robust to time series application for the period Q3-1997 to Q3-2015, where a stationary, long-run relationship between economic growth, public and private sector investment, and exports and imports of goods and services is found. This period also marks a strong unidirectional causality running from both public and private investments to GDP growth. Capital is increasingly driving growth, but at the expense of the agriculture sector and the labor market. It appears that for growth to be all inclusive, capital utilization needs to be complemented by strategies to absorb
any excess capacity in agriculture and the labor market. One way to address this is for government to use policy to steer the productive system toward the adoption of capital-led, labor-intensive technologies, in tandem with scaling up public infrastructural investment.
Drafts by Wilson Asiimwe
shifting a quarter of the aid funds to the local actors, performance has remained low. By 2021 less than one percent of the humanitarian aid was being allocated to local actors. Though recent scholars have postulated that redirecting aid funds to local actors might be beneficial, there is limited quantitative literature to support this proposal, especially for the case of Uganda. Based on this background, this paper uses a Dynamic Computable General Equilibrium model to assess the macroeconomic impacts of shifting aid funds from traditional spending architecture to direct cash transfers for households in Uganda.
The findings reveal that shifting aid funds to local actors (households) provides macroeconomic benefits to the economy and generates spillover effects to non-recipient households and other economic agents. Financing the cash transfers by reducing allocations to government and so-called ‘Non-Profit Institutions Service Households’ increases tax revenues, household incomes and savings. However, employment and economic growth decline as the actual appreciation of the exchange rate reduces international competitiveness. The decline in economic growth is driven by a decline in industry and service sector GDP as agricultural GDP increases. The alternative scenario of financing social cash transfers by reducing the overheads of offshore aid is the most effective in improving economic growth, household incomes, government tax returns, employment and household savings and investment. International humanitarian donors and aid organisations are urged to consider re-directing aid funds from the overseas overhead costs to local actors through direct SCT to vulnerable households. This will improve household welfare, investment and employment and accelerate economic growth.
crisis are severe, erasing poverty gains of the past 10 years, and reaching well beyond Kampala. Using household-level information from the 2016/17 Uganda National Household survey, we explore four different transfer schemes that the government might use to offset the poverty consequences of the crisis: (i) a universal transfer to all households based on their adult equivalence size, but excluding households with income from employment in the public sector or a public sector pension; (ii) a transfer of the same size as in (i), but targeted to only those households that were poor before the crisis began; (iii) an expansion of the SAGE grant to all those 65 years old and older; and (iv) a labor-intensive public works program directed at the hardest hit
urban areas.
This paper and accompanying excel workbook describe the construction of a SAM for Uganda for the 2016/17 financial year. We discuss the structure of the SAM as the various sources of data. The data sources
include the Supply Use Table for 2016/17, Government Financial Statistics (GFS), Ugandan National Household Survey, Balance of Payments and financial data. The development of the SAM is completed in 2 steps. First a Macro SAM is developed. This Macro SAM is then disaggregated further by disaggregating the activities and commodities accounts, labour income and expenditure, and the household accounts.
We do not present the Full SUT and SAM as part of this paper. To access the Full SUT, contact the Ugandan Bureau of Statistics (UBOS)1, and to access the Full SAM, contact the Ministry of Finance, Planning and Economic Development (MoFPED).
and output to strengthen effectiveness of monetary policy.
double the returns to labor. These results are robust to time series application for the period Q3-1997 to Q3-2015, where a stationary, long-run relationship between economic growth, public and private sector investment, and exports and imports of goods and services is found. This period also marks a strong unidirectional causality running from both public and private investments to GDP growth. Capital is increasingly driving growth, but at the expense of the agriculture sector and the labor market. It appears that for growth to be all inclusive, capital utilization needs to be complemented by strategies to absorb
any excess capacity in agriculture and the labor market. One way to address this is for government to use policy to steer the productive system toward the adoption of capital-led, labor-intensive technologies, in tandem with scaling up public infrastructural investment.