993 resultados para Agricultural price supports
Resumo:
The primary purpose of this brief is to provide various statistical and institutional details on the development and current status of the public agricultural research system in Cape Verde. This information has been collected and presented in a systematic way in order to inform and thereby improve research policy formulation with regard to the Cape Verdean NARS. Most importantly, these data are assembled and reported in a way that makes them directly comparable with the data presented in the other country briefs in this series. And because institutions take time to develop and there are often considerable lags in the agricultural research process, it is necessary for many analytical and policy purposes to have access to longer-run series of data. NARSs vary markedly in their institutional structure and these institutional aspects can have a substantial and direct effect on their research performance. To provide a basis for analysis and cross-country, over-time comparisons, the various research agencies in a country have been grouped into five general categories; government, semi-public, private, academic, and supranational. A description of these categories is provided in table 1.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.
Resumo:
The present paper makes progress in explaining the role of capital for inflation and output dynamics. We followWoodford (2003, Ch. 5) in assuming Calvo pricing combined with a convex capital adjustment cost at the firm level. Our main result is that capital accumulation affects inflation dynamics primarily through its impact on the marginal cost. This mechanism is much simpler than the one implied by the analysis in Woodford's text. The reason is that his analysis suffers from a conceptual mistake, as we show. The latter obscures the economic mechanism through which capital affects inflation and output dynamics in the Calvo model, as discussed in Woodford (2004).
Resumo:
We study the effect of regional expenditure and revenue shocks on price differentials for47 US states and 9 EU countries. We identify shocks using sign restrictions on the dynamicsof deficits and output and construct two estimates for structural price differentials dynamics which optimally weight the information contained in the data for all units. Fiscal shocks explain between 14 and 23 percent of the variability of price differentials both in the US and in the EU. On average, expansionary fiscal disturbances produce positive price differential responses while distortionary balance budget shocks produce negative price differential responses. In a number of units, price differential responses to expansionary fiscal shocks are negative. Spillovers and labor supply effects partially explain this pattern while geographical, political, and economic indicators do not.
Resumo:
I study a repeated buyer-seller relationship for the exchange of a givengood. Asymmetric information over the buyer's reservation price, which issubject to random shocks, may lead the seller to use a rigid pricing policydespite the possibility of making higher profits through price discriminationacross the different satates of the buyer's reservation price. The existence of a flexible price subgame perfect equilibrium is shown for the buyerssufficiently locked-in. When the seller faces a population of buyers whose degree of involvmentin the relatioship is unknown, the flexible price equilibrium is notnecessarily optimal. Thus tipically the seller will prefer to use therigid price strategy. A learning process allowing the seller to screenthe population of buyers is derived abd the existence of a switching pointbetween the two regimes (i.e. price rigidity and price felxibility) isshown.
Resumo:
This paper analyzes the different equilibria in rural-urban migrationsand political redistribution that result from the interaction betweenincreasing political returns, the distribution of land, and creditmarket imperfections. Governments that put a special weight on thewelfare of urban workers when setting agricultural prices generate apolitical externality in the urban sector, giving peasants anincentive to migrate in anticipation of policy determination. Ifcredit markets are imperfect, land ownership confers higherproductivity to peasants, who require large price changes to migrate.In this context, land inequality would lead to large migrations and tolarge policy change, while an egalitarian land distribution would leadto no migration and to a small policy change. This interaction shedslight on the contrasting experience of Latin America and East Asia atthe outset of World War II.
Resumo:
Audit report on the Iowa Agricultural Development Authority for the year ended June 30, 2008
Resumo:
I study monotonicity and uniqueness of the equilibrium strategies in a two-person first price auction with affiliated signals. I show thatwhen the game is symmetric there is a unique Nash equilibrium thatsatisfies a regularity condition requiring that the equilibrium strategies be{\sl piecewise monotone}. Moreover, when the signals are discrete-valued, the equilibrium is unique. The central part of the proof consists of showing that at any regular equilibrium the bidders' strategies must be monotone increasing within the support of winning bids. The monotonicity result derived in this paper provides the missing link for the analysis of uniqueness in two-person first price auctions. Importantly, this result extends to asymmetric auctions.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.
Resumo:
The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.