Food Security Crop Price Transmission and Formation in Nigeria

The three studies in this dissertation explore the current conditions and operations of markets for seven key food security crops (cassava, cowpeas, maize, millet, rice, sorghum, and yams) in Nigeria. Chapter 2 is an empirical analysis of the current agricultural statistics system in Nigeria. A number of sources gather and report agricultural statistics for the country. Since there has not been an agricultural census implemented there for multiple decades, however, there is no objective source for data verification. Therefore, this study uses two additional types of “on the ground information” to assess if agricultural production estimates reflect growing conditions: prices and remote sensing data in the form of the normalized difference vegetation index (NDVI). The results show that existing production estimates are poorly correlated with both prices and the NDVI. Prices and the NDVI data are highly correlated, however. These findings imply that existing production estimates do not reflect growing conditions, and, therefore, are of poor quality. Chapter 3 is a comprehensive analysis of crop price transmission from global and neighbor country prices to Nigerian commercial hub and urban markets, and from commercial hubs to other urban and rural markets within the country. The results show that tradability matters for price transmission, but that tradability varies across crops and scopes of markets. Nigerian urban rice prices are highly correlated with prices on global markets and those in neighboring countries. Coarse grain prices appear disconnected from global markets, however, but move closely with those in neighboring countries. Large margins were estimated for prices of rice imported from global markets (in all regions), and for coarse grains to Southern Nigerian markets only. The existence of large margins implies that there are transactions costs and/or quality premiums that vary systematically with the world price, and/or mark-ups by traders with market power in these markets. While domestic market prices are almost always cointegrated, perfect price transmission is generally found only between commercial hubs and other urban markets. Moreover, long lags were found for price transmission across all scopes of markets, but especially between urban and rural prices in some regions. These results imply that local conditions (e.g., weather) are relatively more important than external market prices for explaining price variation in rural markets, especially in the short-run. Chapter 4 incorporates NDVI data into price formation models to estimate whether observable growing conditions explain price variation in Nigerian food security crop markets. Four issues related to use of NDVI data that exist within the literature are investigated: whether NDVI is a valid proxy for expected production, how NDVI is a proxy for seasonality, the relationship between market size and the area scope used to average NDVI values across space, and if anomalous harvest expectations can change long-run price variation and price relationships between markets. The results show that information on growing conditions is more informative for isolated than interconnected markets. Even for those local prices, however, other non-weather and non-external market price factors are relatively more important for explanation of price variation. An implication of these results is that Nigeria cannot plausibly rely solely on direct imports from global markets to meet short-run demand during future weather shock periods. Thus, storage is required to ensure stability of food security, either for imports or domestically produced surpluses acquired in non-crisis periods. Given the isolation of rural markets, local and on-farm stocks are at least as important as large facilities in commercial hubs. Improvement of village level and on-farm storage systems and elimination of other market distortions that inhibit trade between urban and rural markets would make public storage less needed. The findings on poor quality of agricultural statistics indicate a clear priority to improve agricultural data, to facilitate better planning of any food security strategies. A combination of surveys with remote sensed and crowd sourced data may improve feasibility in the funding constrained environment

Pleiotropic contribution of MECOM and AVPR1A to aggression and subcortical brain volumes

Reactive and proactive subtypes of aggression have been recognized to help parse etiological heterogeneity of this complex phenotype. With a heritability of about 50%, genetic factors play a role in the development of aggressive behavior. Imaging studies implicate brain structures related to social behavior in aggression etiology, most notably the amygdala and striatum. This study aimed to gain more insight into the pathways from genetic risk factors for aggression to aggression phenotypes. To this end, we conducted genome-wide gene-based cross-trait meta-analyses of aggression with the volumes of amygdala, nucleus accumbens and caudate nucleus to identify genes influencing both aggression and aggression-related brain volumes. We used data of large-scale genome-wide association studies (GWAS) of: (a) aggressive behavior in children and adolescents (EAGLE, N = 18,988); and (b) Magnetic Resonance Imaging (MRI)-based volume measures of aggression-relevant subcortical brain regions (ENIGMA2, N = 13,171). Second, the identified genes were further investigated in a sample of healthy adults (mean age (SD) = 25.28 (4.62) years; 43% male) who had genome-wide genotyping data and questionnaire data on aggression subtypes available (Brain Imaging Genetics, BIG, N = 501) to study their effect on reactive and proactive subtypes of aggression. Our meta-analysis identified two genes, MECOM and AVPR1A, significantly associated with both aggression risk and nucleus accumbens (MECOM) and amygdala (AVPR1A) brain volume. Subsequent in-depth analysis of these genes in healthy adults (BIG), including sex as an interaction term in the model, revealed no significant subtype-specific gene-wide associations. Using cross-trait meta-analysis of brain measures and psychiatric phenotypes, this study generated new hypotheses about specific links between genes, the brain and behavior. Results indicate that MECOM and AVPR1A may exert an effect on aggression through mechanisms involving nucleus accumbens and amygdala volumes, respectively

Heritability and genome-wide association analyses of sleep duration in children: The EAGLE consortium

Study Objectives: Low or excessive sleep duration has been associated with multiple outcomes, but the biology behind these associations remains elusive. Specifically, genetic studies in children are scarce. In this study, we aimed to: (1) estimate the proportion of genetic variance of sleep duration in children attributed to common single nucleotide polymorphisms (SNPs), (2) identify novel SNPs associated with sleep duration in children, and (3) investigate the genetic overlap of sleep duration in children and related metabolic and psychiatric traits. Methods: We performed a population-based molecular genetic study, using data form the EArly Genetics and Life course Epidemiology (EAGLE) Consortium. 10,554 children of European ancestry were included in the discovery, and 1,250 children in the replication phase. Results: We found evidence of significant but modest SNP heritability of sleep duration in children (SNP h2 0.14, 95% CI [0.05, 0.23]) using the LD score regression method. A novel region at chromosome 11q13.4 (top SNP: rs74506765, P = 2.27e-08) was associated with sleep duration in children, but this was not replicated in independent studies. Nominally significant genetic overlap was only found (rG = 0.23, P = 0.05) between sleep duration in children and type 2 diabetes in adults, supporting the hypothesis of a common pathogenic mechanism. Conclusions: The significant SNP heritability of sleep duration in children and the suggestive genetic overlap with type 2 diabetes support the search for genetic mechanisms linking sleep duration in children to multiple outcomes in health and disease