Foreign Ownership and Wages in British Establishments

This paper uses the 1990-1998 Workplace Employee Relations Survey (WERS) panel data set to show that foreign establishments in Britain pay 13 per cent higher wages than domestic establishments. However, the differential disappears when we control for the skill structure within establishments.

Spatial Inequality for Manufacturing Wages in Five African Countries

wage inequality, earnings function, location, Africa

Trade, FDI, Growth and Poverty in Bolivia

After several decades of “state-capitalism” characterized by import substitution policies, Bolivia implemented in 1985 a New Economic Policy (NEP) following neo-liberal ideas of free trade, privatization, and liberalization of capital flows. It was hoped that the opening up of the economy would attract foreign direct investment (FDI) which in turn would help modernize Bolivian industry, improve productivity, increase exports, stimulate growth, and reduce poverty. This paper investigates to what extent this actually happenedTrade, Foreign Direct Investment, Poverty, Inequality, Bolivia

Development Finance Institutions and the Coronavirus Crisis

Key messages: Development finance institutions (DFIs) are mandated by their shareholders to provide finance to the private sector (usually at commercial terms, but subsidised implicitly), crowd in private sector finance and have a development impact; While DFIs aim to be additional to the market, they have not been sufficiently counter-cyclical in past crises. That has to change,as poor country firms and their workers face major hardship now. Today’s crisis is larger than those in the past; We suggest shareholders provide regulatory and financial space for DFIs to fast-track new investments, allow for some repaymentpostponements and announce a Bounce Back Better facility, to save companies and workers from bankruptcy and to protectprevious transformation efforts so that the bounce-back is faster and better

Shaping the Macroeconomy of Low- and Middle-income Countries in Response to Covid-19

There is heterogeneity in the magnitude of the pandemic’s shortterm impact across the five low- and middle-income countries (L&MICs) that are the focus of this synthesis paper: Bangladesh, Kenya, Peru, Sri Lanka and Tanzania. Based on pre-Covid-19 forecasts, Peru was supposed to grow by 3.6% but the pandemic led to an actual contraction of the Peruvian economy by 11% – suggesting 15 percentage points loss of growth due to the pandemic. Similarly, Sri Lanka was forecast to grow by 1.5% but the pandemic led to a -3.6% economic contraction in 2020 – the worst in the country’s 73 years of independence. Meanwhile, Tanzania grew by 4.8% in 2020, which is only about 1 percentage point lower than pre-Covid-19 forecasts. Structural characteristics, initial macroeconomic conditions, and the size and quality of policy responses largely shaped the absolute and distributional impact of Covid-19 in the five L&MICs. Impacts from sharp declines in tourism activities in 2020 were offset partly by increased global demand from their major exports of agricultural products (e.g., Kenya, Peru) and gold (e.g., Tanzania). Bangladesh benefitted from a quick recovery of major trading partners’ demand for garments (comprising 90% of Bangladeshi export).IDRC | CRD

Use of a Bayesian belief network to predict the impacts of commercializing non-timber forest products on livelihoods

Commercialization of non-timber forest products (NTFPs) has been widely promoted as a means of sustainably developing tropical forest resources, in a way that promotes forest conservation while supporting rural livelihoods. However, in practice, NTFP commercialization has often failed to deliver the expected benefits. Progress in analyzing the causes of such failure has been hindered by the lack of a suitable framework for the analysis of NTFP case studies, and by the lack of predictive theory. We address these needs by developing a probabilistic model based on a livelihood framework, enabling the impact of NTFP commercialization on livelihoods to be predicted. The framework considers five types of capital asset needed to support livelihoods: natural, human, social, physical, and financial. Commercialization of NTFPs is represented in the model as the conversion of one form of capital asset into another, which is influenced by a variety of socio-economic, environmental, and political factors. Impacts on livelihoods are determined by the availability of the five types of assets following commercialization. The model, implemented as a Bayesian Belief Network, was tested using data from participatory research into 19 NTFP case studies undertaken in Mexico and Bolivia. The model provides a novel tool for diagnosing the causes of success and failure in NTFP commercialization, and can be used to explore the potential impacts of policy options and other interventions on livelihoods. The potential value of this approach for the development of NTFP theory is discussed

Shaping the Macro-Economy in Response to COVID-19: A Responsible Economic Stimulus, a Stable Financial Sector and a Revival in Exports

Ensuring a healthy macro-economy is crucial for a high-quality recovery from Covid-19. Engineering appropriate stimulus packages, keeping a stable financial sector and reviving high value-added exports are core tasks of governments across the world as they also try to recover from the economic effects of the pandemic in 2020–2023. Unfortunately, the context in low-income settings looks more depressed because of lack of finance and more vulnerable economies. Informing policy options for a better macro-economy in lower-income settings is a core task of an International Development Research Centre (IDRC)-funded project undertaken by the Overseas Development Institute (ODI) and five other think-tanks. This paper presents a methodology and a range of methods to provide quality research and analysis that can underpin such policy advice.IDRC | CRD

The Global Financial Crisis and Developing Countries: Phase 2 Synthesis

When the global financial crisis broke out in earnest in September 2008, it quickly became clear that developing countries would also be affected, but that the impacts would vary markedly. The Overseas Development Institute (ODI) coordinated a multi-country study over January-March 2009 involving developing country teams in 10 countries. This showed that, while the transmission mechanisms were similar in each (trade, private capital flows, remittances, aid), the effects varied by country, and much was not yet visible. As such, further country-specific monitoring was required. Most findings suggested that, as a result of time lags, the worst effects were yet to come. This synthesis of the effects of the global financial crisis on developing countries updates the description of the economic and social situation during the course of the crisis in 11 countries