How Strong Do Global Commodity Prices Influence Domestic Food Prices in Developing Countries? A Global Price Transmission and Vulnerability Mapping Analysis

This paper analyzes the transmission from global commodity to domestic food prices for a large set of countries. First, a theoretical model is developed to explain price transmission for different trade regimes. Drawing from the competitive storage model under rational expectations, it is shown that domestic prices can respond instantaneously to global prices even if no trade takes place but future trade is expected. Using a global database on food prices, we construct national and international grain price indices. With an autoregressive distributed lag model, we empirically detect countries in which food prices are influenced by global commodity prices, including futures prices. Mapping transmission elasticities with the size of the population below the poverty line which spends typically a large share of its income on food, we are able to estimate the size of vulnerable population. Our empirical analysis reveals that 90 percent of the global poor (income below 1.25$/day) live in countries where domestic food prices respond to international prices - but the extent of transmission varies substantially. For 360 million poor people, international prices transmit to their country at rates of 30 percent or higher within three months

Impact of combined 18F-FDG PET/CT in head and neck tumours

To compare the interobserver agreement and degree of confidence in anatomical localisation of lesions using 2-[fluorine-18]fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) and 18F-FDG PET alone in patients with head and neck tumours. A prospective study of 24 patients (16 male, eight female, median age 59 years) with head and neck tumours was undertaken. 18F-FDG PET/CT was performed for staging purposes. 2D images were acquired over the head and neck area using a GE Discovery LS™ PET/CT scanner. 18F-FDG PET images were interpreted by three independent observers. The observers were asked to localise abnormal 18F-FDG activity to an anatomical territory and score the degree of confidence in localisation on a scale from 1 to 3 (1=exact region unknown; 2=probable; 3=definite). For all 18F-FDG-avid lesions, standardised uptake values (SUVs) were also calculated. After 3 weeks, the same exercise was carried out using 18F-FDG PET/CT images, where CT and fused volume data were made available to observers. The degree of interobserver agreement was measured in both instances. A total of six primary lesions with abnormal 18F-FDG uptake (SUV range 7.2–22) were identified on 18F-FDG PET alone and on 18F-FDG PET/CT. In all, 15 nonprimary tumour sites were identified with 18F-FDG PET only (SUV range 4.5–11.7), while 17 were identified on 18F-FDG PET/CT. Using 18F-FDG PET only, correct localisation was documented in three of six primary lesions, while 18F-FDG PET/CT correctly identified all primary sites. In nonprimary tumour sites, 18F-FDG PET/CT improved the degree of confidence in anatomical localisation by 51%. Interobserver agreement in assigning primary and nonprimary lesions to anatomical territories was moderate using 18F-FDG PET alone (kappa coefficients of 0.45 and 0.54, respectively), but almost perfect with 18F-FDG PET/CT (kappa coefficients of 0.90 and 0.93, respectively). We conclude that 18F-FDG PET/CT significantly increases interobserver agreement and confidence in disease localisation of 18F-FDG-avid lesions in patients with head and neck cancers