In response to the Stabroek News article dated August 18, 2025, which claims that the Government of Guyana has failed to provide evidence of creating 50,000 jobs, this commentary offers a data-informed rebuttal grounded in a rigorous extrapolation methodology and sectoral analysis.
𝐊𝐞𝐲 𝐌𝐞𝐬𝐬𝐚𝐠𝐞
Between 2021 and 2025, the PPP/C Government’s expansionary economic policies and strategic public investments—particularly in infrastructure, housing, health, and education—have led to the creation of an estimated ≥70,000 sustainable jobs across the Guyanese economy. This outcome exceeds the 50,000-job target outlined in the party’s 2020 manifesto.
Importantly, this estimate is not based on anecdotal claims, but rather on a methodologically sound extrapolation of available economic and sectoral data. The analysis uses the 2021 Q3 Guyana Labour Force Survey (GLFS) as a baseline, supported by a variance analysis with Bank of Guyana labour force and population estimates. Sector-specific indicators—such as growth in construction, agriculture, tourism, housing finance, and transport—were used to infer employment trends.
The estimate is further corroborated by 67,905 new employees registered with the National Insurance Scheme (NIS) between ages 16–59. When adjusted for expatriate labour, the total employment estimate of 72,293 implies approximately 4,388 expatriates—reinforcing the credibility of the ≥70,000 figure.
It is important to note that this overall estimate also includes the restoration of approximately 40,000 jobs lost between 2015 and 2020 under the APNU+AFC administration. These were jobs that had been displaced due to policy reversals, economic contraction, and underinvestment in key sectors during that period.
These estimates are conservative by design, excluding employment contributions from the manufacturing and services sub-sectors, as well as part-time and informal jobs. As such, the actual employment impact may be even greater.
𝐒𝐞𝐜𝐭𝐨𝐫𝐚𝐥 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬 𝐭𝐨 𝐉𝐨𝐛 𝐂𝐫𝐞𝐚𝐭𝐢𝐨𝐧
• Construction Sector: Grew by 180% between 2020 and 2024, driven by public infrastructure projects and housing development. Over 30,000 jobs were conservatively estimated from more than 6,300 public contracts, assuming an average of five jobs per project.
• Housing Construction: A 70% increase in residential mortgages—from G$90B in 2020 to G$153B in 2024—correlates with the construction of 5,000 low-income homes, generating an estimated 25,000 jobs. This correlation was calculated using a linear model, yielding a coefficient of 1.00, indicating a perfect positive relationship between mortgage growth and employment.
• Agriculture Sector: Benefited over 75,572 persons through job creation and capacity-building initiatives whereby (as per budget estimates KPIs):
– 461 graduates were equipped with skills to profitably manage their own agri-business;
– 44,160 farmers trained in sustainable agriculture practice;
– 673 farmers certified to produce wholesome food and agricultural commodities for export;
– 761 farmers trained in aquaculture;
– 29,517 licenses processed by the fisheries department.
• Tourism and Hospitality: Added approximately 7,300 jobs through targeted policies and government-sponsored programmes.
• Transport Sector: Between 2021 and 2024, approximately 20,000 hire cars and minibuses were registered. Even assuming that 50% were replacements by existing drivers/owners, this implies the addition of at least 10,000 new drivers to the workforce—highlighting the sector’s contribution to informal and service-based employment.
• Other Key Sectors: Agriculture, forestry and fishing; mining and quarrying; manufacturing; wholesale and retail trade; transportation and storage; and accommodation and food services accounted for 83% of total employment in 2021, with a combined growth of 49.8% between 2020 and 2024.
𝗖𝗼𝗻𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝘃𝗲 𝗘𝘀𝘁𝗶𝗺𝗮𝘁𝗲𝘀, 𝗥𝗲𝗮𝗹 𝗜𝗺𝗽𝗮𝗰𝘁
These estimates exclude employment contributions from the manufacturing and services sub-sectors, as well as expatriate and part-time labour—making the figures conservative by design. For instance, the 67,905 new employees registered with the National Insurance Scheme (NIS) between ages 16–59 corroborate the broader employment estimate of 72,293, implying approximately 4,388 expatriates.
𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻: 𝗔 𝗣𝗹𝗮𝘂𝘀𝗶𝗯𝗹𝗲 𝗮𝗻𝗱 𝗗𝗲𝗳𝗲𝗻𝘀𝗶𝗯𝗹𝗲 𝗘𝘀𝘁𝗶𝗺𝗮𝘁𝗲
The claim that the government has not provided evidence of job creation is not only misleading—it ignores the methodological rigor and data triangulation employed in this analysis. By using extrapolation techniques anchored in official statistics and sectoral performance indicators, this review demonstrates that the government’s reported employment gains are both plausible and defensible.
In sum, this analysis underscores the importance of reliable data, methodical reasoning, and economic modeling in assessing national employment dynamics. It also reaffirms the pivotal role of targeted public investment in driving inclusive growth and sustainable development.
𝗠𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝘆: 𝗘𝘃𝗶𝗱𝗲𝗻𝗰𝗲-𝗕𝗮𝘀𝗲𝗱 𝗘𝘅𝘁𝗿𝗮𝗽𝗼𝗹𝗮𝘁𝗶𝗼𝗻
This analysis employs the 2021 Q3 Guyana Labour Force Survey (GLFS) by the Bureau of Statistics as its baseline. A variance analysis was conducted between GLFS and Bank of Guyana (BoG) labour force and population estimates to validate assumptions. Sector-specific indicators—such as growth rates, investment volumes, and employment ratios—were used to extrapolate employment trends across key industries from 2021 to 2025.
This method acknowledges the limitations of direct enumeration and instead leverages economic proxies to estimate employment outcomes. It is a widely accepted technique in policy analysis and macroeconomic modeling.
Data triangulation is a methodological approach that enhances the credibility and reliability of an analysis by combining multiple sources of information to examine a single issue. In this case, the job creation estimate is supported by:
• Official labour force data (GLFS 2021 Q3)
• Macroeconomic indicators (e.g., sectoral growth, mortgage volumes)
• Administrative records (e.g., NIS registrations)
• Extrapolation techniques (e.g., employment per housing unit or contract)
By integrating these diverse data points, the analysis provides a more robust and defensible estimate of employment outcomes—especially in the absence of real-time, granular data.