Peter Windsor, Jeffery Yong, and Michelle Chong-Tai Bell
The paper explores the use of accounting standards for insurer solvency assessment in the context of the implementation of IFRS 17. The paper is based on the results of a survey of 20 insurance supervisors. Overall, IFRS 17 is a welcome development but there will be challenges of implementation. Not many insurance supervisors currently intend to use IFRS 17 as a basis for solvency assessment of insurers. Perceived shortcomings can be overcome by supervisors providing clear specifications where the principles-based standard allows a range of approaches. Accounting standards can provide a ready-made valuation framework for supervisors developing new solvency frameworks.
This paper has examined Papua New Guinea's historical economic growth patterns through a simple growth accounting framework. The analysis shows that swings in growth are mostly accounted for by a significant slowdown in capital input and lower Total Factor Productivity (TFP) growth. It also suggests that raising real GDP growth will require increases in both investment levels and productivity. With a ratio of investment to GDP of 13 percent during the last decade, significantly higher productivity growth and investment will be needed to sustain GDP growth rates at 5 percent or higher. The historical performance also indicates that, in the absence of structural reforms and strong institutions, higher rates of productivity growth will be hard to achieve.
This Selected Issues paper on Papua New Guinea reports that although economic cycles have generally paralleled the many mineral sector booms and busts, the downward trend in growth rates may reflect other factors. Papua New Guinea’s economy is dominated by a large labor-intensive agricultural sector and a capital-intensive oil and minerals sector. The formal sector consists of enclave extractive industries, cash crop production, and a small, import-substituting manufacturing sector. The importance of the agriculture sector is about the same as at independence, reflecting structural impediments that have deterred more rapid growth.
This paper investigates convergence and dynamic effects of human and physical capital on growth, in WAEMU countries. Using recently developed models for panel data and a growth accounting model, the study finds that growth is largely explained by changes in literacy rates and factor accumulation, but not by growth of total factor productivity (TFP). Nevertheless, the panel estimation identifies aid, government spending, credit to the private sector, and openness as positive determinants of TFP growth, and government deficits as a negative determinant. The study also finds that per capita income in lower-income WAEMU countries converge to per capita income in higher-income ones when economic policies are similar. These results suggest opportunities for policymakers to enhance growth and convergence.
The IMF Research Bulletin, a quarterly publication, selectively summarizes research and analytical work done by various departments at the IMF, and also provides a listing of research documents and other research-related activities, including conferences and seminars. The Bulletin is intended to serve as a summary guide to research done at the IMF on various topics, and to provide a better perspective on the analytical underpinnings of the IMF’s operational work.
A growth accounting exercise is conducted for 88 countries for 1960-94 to examine the source of cross-country differences in total factor productivity (TFP) levels. Two differences distinguish this analysis from that of the related literature. First, the critical technology parameter—the share of physical capital in real output—is econometrically estimated and the usual assumption of identical technology across regions is relaxed. Second, while the few studies on the determinants of cross-country differences in TFP have focused on growth rates of real output this analysis is on levels. Recent theoretical as well as empirical arguments point to the level of TFP as the more relevant variable to explain.