Factors that contribute to the internationalization of the Qatari Small and Medium Enterprises

This study aims to identify the factors that the Qatari government can contribute to Qatar’s internationalization of Small-Medium Enterprises (SME). In addition, it highlights the current role played with a variation of the future proposed programs. The obstacles faced by entrepreneurs also have been identified, and was accompanied by counterparts’ views from the country’s officials. This study involved an online survey shared with 100 business owners and people working in the private sectors targeted through different mediums with help from Qatar Development Bank and their subsidiaries. The overall conclusion from the data analyzed is that there are still missing factors that the country lacks regulations, facilities, and education. However, there is evidence that the Qatari regulator moves in the right direction with the different initiatives and programs. Therefore, even though there are existing facilities, the programs offered do not fit the entrepreneurs’ needs. The entrepreneurs lack the managerial and marketing skills and the power in bargaining and negotiation with external stakeholders. The main recommendation is to set national private sector/SME advancement techniques within the broader national advancement translated in a centralized portal based on the overall conclusion. Different recommendations have been proposed to provide proper training programs’ implementation plan. The proposals include the capacity of the Qatari government to actualize sound macroeconomic arrangements. The training programs to involve the teachers’ development expand the learner’s ranks, content sharing facility, and instructional methods redesigning. In addition, accessibility to loans and advanced finance equity, mainly to medium and long-term opportunities to grow SMEs’ exchange and venture capacity align with the Qatari National Vision 2030, whereas keeping up sound government accounts will offer assistance to the accessibility of finance for improvement purposes.

Prioritizing School Finance Equity during an Economic Downturn: Recommendations for State Policy Makers

State budgets temporarily crashed amid the COVID-19 pandemic and economic shutdown, placing education funding at risk. To demonstrate implications for school finance, we show that (1) school districts are racially segregated along class lines; (2) higher-poverty districts receive a greater share of funds from state, as opposed to local sources, making them especially vulnerable during economic downturns; and (3) many states made across-the-board K-12 budget reductions following the Great Recession, but those cuts disproportionately impacted high-poverty districts. A decade later, state legislators may face similar fiscal challenges. Instead of enacting acrossthe-board cuts, states can identify specific funding programs that already benefit lower-poverty districts or wealthier students. We demonstrate how this approach would work under different state finance models and offer recommendations for state policy makers.

Does the Measurement Matter? Assessing Alternate Approaches to Measuring State School Finance Equity for California’s Local Control Funding Formula

Scholars have not reached consensus on the best approach to measure state school finance equity. The regression-based approach estimates the relationship between district poverty rate and funding level, controlling for other district cost factors. A second commonly used approach involves estimating the weighted average funding level for low-income students or other subgroups. Meanwhile, policymakers have preferences for their own data systems and poverty indicators when reading reports and assessing progress. We constructed parallel, district-level panel data sets using data from the California Department of Education and the U.S. Census. We estimated changes over time in district-level school finance equity under California’s Local Control Funding Formula, using multiple school finance measurement approaches, with each of the two data sets. Our results show that different methods and analytic choices result in policy-relevant differences in findings. We discuss the implications for policy and future research.