آیا درسال 1933 قانونی جدیدبرای کمک به ارزش دارایی واقعی مزارع داده شد: تجزیه و تحلیل منطقه ای
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|6864||2012||16 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Policy Modeling, Volume 34, Issue 6, November–December 2012, Pages 801–816
The proportion of land values generated by farm program payments and farm returns are examined using an extended income capitalization model. The extended income capitalization model addresses the identification issue introduced by the counter-cyclical nature of farm program payments and farm returns. Procedures are presented that allow the estimation of agriculture land value shares without requiring explicit knowledge or assumptions with respect to the net land rental shares of farm returns or farm program payments. Results from the panel recursive or triangular-structure simultaneous equation model applied to 48 states in the U.S. for the period 1938–2010 indicate on average 24–29.2 percent and 76–70.8 percent of the agricultural land values can be identified with farm program payments and farm returns, respectively. Spatially, at the resource regional level the contribution of farm program payments was as low as 20.5 percent in the Eastern Upland region compared to a high of 69 percent in the Mississippi Seaboard region.
In the last century, American agriculture aided by federal farm programs has undergone an impressive transformation with much debate about structural changes. In 1933 among the first pieces of New Deal legislation proposed by incoming President Franklin D. Roosevelt, was a farm program designed to address declines in farm prices and net farm income. Since 1933, the design of federal farm policy changes or remains status quo approximately every five years with the authorization of a new farm bill. Aside from the domestic policy implications, considerable interest can be found among our trading partners regarding the impact U.S. farm programs have on world production and international markets. Given this context, interest has grown in understanding how past federal farm programs have affected the structure of agriculture and how future policies could be designed to achieve preferred social outcome. Recently concern has grown about how to redesign federal farm programs to minimize federal program outlays and production impacts for domestic and trade purposes, while at the same time strengthening the survivability or preventing the demise of family farms. Although federal farm programs in the U.S. are rarely intended to alter the structure of U.S. agriculture, the effect of these programs on the structure has long been an economic as well as political concern. Farm commodity programs, once viewed as temporary and supplementary to agricultural earnings, are increasingly considered permanent and of major proportion. Literature (Gardner, 1987 and Sumner, 2003) has examined the cause and effect of U.S. farm commodity programs on U.S. farm structure. Apart from technology the widely held view that a major, if not the most significant mechanism for structural change in agriculture is the effect of federal farm programs on land value or farm real estate. Related concerns have been raised that current congressional emphasis on substantially reducing farm program payments might adversely affect U.S. agricultural land prices. Thus, some portion of expected agricultural subsidies have been discounted in land prices, reducing expected future transfer payments is also likely to decrease agricultural land prices. Given this possibility policy makers are interested in studies estimating the potential magnitude of adverse effects of policy changes upon land values. The results of this study will be of interest to such policy makers in that we present methods to econometrically estimate the share of U.S. and regional agricultural land values resulting from farm program payments. Farm real estate comprises approximately 80 percent of farm assets and it is hypothesized that a large share of the farm program payment is capitalized into these values. Reliably estimating the magnitude of the effect farm program payments have on land value is an empirically challenging task. Both statistical and budgetary-based methodologies have been used to estimate the share of land prices generated by farm program payments and farm returns. Statistically based methods are complicated by the fact that both real per acre farm returns and per acre farm program payments have drifted in the same direction over time but tend to be inversely correlated within any given year. Thus, this extension has the potential problem of identification introduced by the counter-cyclical relationship between expected farm returns and expected farm program payments. To address the identification issue, the econometric estimation uses a recursive/triangular structure simultaneous equation model. This assumption means that unobserved factors can affect both land value and farm program payments, and farm program payments can affect land value directly, but land value cannot affect farm payments directly. An additional complication affecting both the statistical and budget-based approach is the fact that the net land rental share of farm returns and farm program payments are unknown and may differ over time. If an income capitalization approach is to be utilized to directly estimate land values, the net land rental proportion of both farm returns and farm program payments must be assumed or computed. With usual budgeting procedures, erroneous assumptions with respect to the net rental proportions, may lead to serious errors in an estimate of the share of land values generated by farm program payments. It circumvents this complication by demonstrating that elasticities of the land value regression equation provide the desired estimate of land value shares without having to explicitly identify the proportion of gross crop returns and farm program payments that accrue as land rent. Appendix A demonstrates procedures that enable the estimation of agricultural land value shares without having to a priori assumption or identify the net rental share of farm returns and farm program payments. Finally, it is clear that some resource regions in the U.S. are more dependent on farm program payments than others due to differences in the type of agriculture, supported commodities, and the effect of program features. A marginal dollar payment is not expected to affect each resource region's land value in the same magnitude. In addition, given the difference in land values, farm program payments and farm crop receipts (Table 1), the contribution of farm returns and farm program payments to agricultural land values is expected to be different across nine U.S. resource regions. This attempt is to examine for such divergent regional effects by estimating the contribution or share of the expected farm returns and farm program payments for each of the nine resource regions using historical data from 1938 to 2010.he contribution of this paper is three-fold. To present an extended income capitalization model that addresses the identification difficulties introduced by the counter-cyclical relationship between farm program payments and farm returns. Second, present procedures that enable an estimation of the share of land value generated by farm returns and farm programs (Appendix A) without having to explicitly identify or assume crop return or farm program payment land net rental proportions. Finally, estimate the proportion of agriculture land value generated by farm returns and farm program payments across nine U.S. resource regions. These are obtained from partial elasticity estimates of the farm return and farm program payment variables from the panel recursive/triangular structure simultaneous equation econometric model. The next section of the paper presents the extended income capitalization model. Procedures that enable the estimation of the share contribution of farm returns and farm program payments to land values are presented in the appendix. In the data section, the details on the source and construction of the regression variables along with means are discussed. This is followed by the panel recursive/triangular-structure simultaneous equation econometric model to estimate the extended income capitalization model. The results of empirical applications to the nine resource regions and U.S. based on state-level data for the period 1938–2010 are presented in the following section. Finally, general and policy implications are presented.
نتیجه گیری انگلیسی
The role farm program payments play in altering the structure of U.S. agriculture with specific reference to agriculture land value is investigated in this paper. This research is unique in the sense that it uses historical U.S. state level data from 1938 to 2010 to examine the effect of farm program payments and farm returns on value of land across nine resource regions and the U.S. With respect to methodology, procedures are presented that allow the estimation of agriculture land value shares without requiring explicit knowledge or assumptions with respect to the net land rental share of farm returns or farm program payments. A recursive estimation procedure is presented that addresses the identification issue introduced by the counter-cyclical nature of farm program payments and farm returns. Two-way random effects panel econometric procedures that account for spatial and temporal variation have been used to estimate the extended income capitalization land value model. Results from the panel recursive or triangular-structure simultaneous equation model applied to 48 states in the U.S. for the period 1938 to 2010 indicate on average 24–29.2 percent and 76–70.8 percent of the agricultural land value can be identified with farm program payments and farm returns, respectively. The regional analysis indicates the contribution of the farm program payments to agriculture land value varied substantially by region. The contribution of farm program payments was as low as 20.5 percent in Eastern Upland region compared to a high of 69 percent in the Mississippi Seaboard region. Regional differences in the contribution of farm program payments might be due to the differences in the agricultural production systems and also due to non-availability of program payments for certain crops or livestock production or lower acreage program crops. The Agriculture Reform, Food and Jobs Act of 2012 represents potentially significant changes in agricultural policies that have included the production controls and price support mechanism's introduced in the 30s, 40s, and mid 50s; the soil conservation and acreage diversion policies of the 60s, 70s, and mid-80s, and the lower commodity price and income support decoupling policies of mid 80s, 90s, and 2000. The 2012 farm bill would end direct payments, streamline and consolidate programs, and reduce the deficit by $23 billion. The farm bill discussions have been somewhat contentious with strong differences in policy preferences not only between political parties and between the house and senate versions but also across regions and producer groups. The sometimes heated nature of the policy debates between regional and crop specific groups is not surprising given the results of this paper. The different regional effects of these policies in general and upon farm land value in particular would indicate some regions could be more adversely and severely affected than others by the proposed reductions in farm program payments given that that farm land and buildings comprise approximately 80 percent of farm assets. This research has several policy implications. First, the result of the study suggests the contributions of the farm program payments to land values varied substantially by region. Due to the differential estimated effect of farm program payments upon land value across regions, it is not surprising that producer groups and congressman from some regions have so strongly opposed provisions that reduce the relatively high transfer payments currently being funneled into their regions. Based on data from 48 states in the U.S. for the period 1938–2010, the contribution of farm program payments ranged from 23 to 70 percent across regions with the larger estimated effect (over a 50% farm program payment agricultural use share) occurring in the Southern Plains and the Mississippi Seaboard regions perhaps explaining why groups from these regions have so strongly opposed significant reforms while groups from the Heartlands and other regions have less stridently opposed the reform. Indeed, given the results of this study, it is likely that substantial cost reductions in the farm program would disproportionately affect the Southern Plains and Mississippi Seaboard regions while having less painful effects upon the crop producing regions of the Midwest. Secondly, the mixed signs on the farm returns variable in the farm program payment equation suggest the counter cyclic nature of farm program payments and farm returns is not consistent across all the resource regions. This indicates that not all farm program payments are paid when the producers are faced with risky situations or needs. Finally, our results do not quantify changes in the share of contribution of farm program payments to the value of land over time. This would be a potentially valuable and fruitful research topic although the lack of historical data on the effect of region specific changes in different types of farm policies may make it difficult to quantify the contribution of the different policies on land value across size groups, commodities, and regions. A related complication is that the total effect of historical agricultural policy cannot be directly assessed by examining farm program payments. A recent example would be the U.S. renewable fuels mandate which is largely credited with causing the recent years’ spike in crop prices that have been followed by substantial increases in agricultural land value. In this case the approach of this paper would have attributed much of the recent increase in real land price to increases in expected farm crop receipts rather than occurring as a result of governmental policy.