绍兴市土地利用时空变化研究

[目的]探讨经济发达地区土地利用变化时空规律,为城市发展提供合理土地利用政策,同时优化土地利用结构以支持经济可持续发展。[方法]通过遥感影像获取长时间序列的土地利用数据,探讨近30多年来绍兴市的土地利用变化,进一步利用土地利用动态变化模型,对绍兴市土地利用变化过程、趋势、变化轨迹进行了深入分析。[结果](1)绍兴市土地利用在1980~2000年相对稳定,在2000年后变化强度逐年增强,2005~2015年土地利用转化量增多和类型多样。绍兴市东北部平原和县区核心区域是经济发达地区土地利用变化的活跃区域,主要是其他类型土地向建设用地转移;(2)1980~2015年绍兴市土地利用变化轨迹主要受到人口增长和GDP增长的影响。[结论]城市化的发展和人口的迅速增长,使城市人口和土地面积迅速增加,造成城市边缘的农业用地转化成了建设用地。经济的发展、科技的进步及政府政策的制定,改变了人们的生活和工作方式,进而影响土地利用类型。     

In the city: The John Lewis partnership and planned shopping centres

A defining feature of large-scale retailing during the period 1950–1980 was the emergence and evolution of planned shopping centres. During the 1950s, department stores in the United States were in the vanguard of this phenomenon. In contrast, British department stores continued operating from traditional high street sites, and had limited opportunities for expansion within planned shopping centres until the 1970s. This paper addresses the connection between department store retailing and the development of the planned shopping centre in Britain from the perspective of one enterprise: the John Lewis Partnership. The article demonstrates that the Partnership was willing to operate department stores within centrally located shopping centres, but was circumspect about operating stores in non-centrally located shopping centres.     

Agricultural productivity growth in Brazil: Large and small farms excel

The long-standing debate on the relationship between farm size and productivity has been generally limited by the range of farm sizes evaluated and the definition of productivity. In this paper we use data from three Brazilian agricultural censuses to address these issues. In particular, we introduce a wider distribution of farm sizes than presently available from the literature and we employ total factor productivity (TFP) as our performance measure. In doing so, we test which farm size class had the highest TFP levels in 1985 and 2006, how factor productivity growth varied within and across farm size classes between those years, and which policy or factor had the greatest productivity enhancing effect. When examining TFP growth, we move beyond the common decomposition into technical and efficiency changes by identifying the complete distribution of farm productivity performances. We find that by 2006 a U-shaped distribution of productivity over farm sizes had emerged. Considerable 1985–2006 TFP growth differences are prevalent; positive rates for the majority accompany stagnant or negative rates for some. Public education investments were associated with faster productivity growth regardless of farm size, while technical assistance’s positive effect and credit’s negative effect were associated with larger farm sizes. The role of specialization varied by size.     

How Fast are Semiconductor Prices Falling?

The Producer Price Index (PPI) for the U.S. suggests that semiconductor prices have barely been falling in recent years, a dramatic contrast to the rapid declines reported from the mid‐1980s to the early 2000s. This slowdown in the rate of decline is puzzling in light of evidence that the performance of microprocessor units (MPUs) has continued to improve at a rapid pace. Over the course of the 2000s, the MPU prices posted by Intel, the dominant producer of MPUs, became much stickier over the chips' life cycle. As a result of this change, we argue that the matched‐model methodology used in the PPI for MPUs likely started to be biased after the early 2000s and that hedonic indexes can provide a more accurate measure of price change since then. MPU prices fell rapidly through 2004 on every price measure we present, with the PPI declining at an even quicker pace than the hedonic indexes. However, from 2004 to 2009, our preferred hedonic index fell faster than the PPI, and from 2009 to 2013 the gap widened further, with our preferred index falling at an average annual rate of 42 percent, while the PPI declined at only a 6 percent rate. Given that MPUs currently represent about half of U.S. shipments of semiconductors, this difference has important implications for gauging the rate of innovation in the semiconductor sector.     

Public Sector Employment and the Skill Premium: Sweden versus the United States 1970–2012

Swedish census data and tax records reveal an astonishing decline in the aggregate skill premium of 30 percent between 1970 and 1990, with only a modest recovery in the next couple of decades. In contrast, the US skill premium rose by around 24 percent over those four decades. A theory that equalizes wages with marginal products can rationalize these disparate outcomes when we replace commonly used measures of total labor supplies by private sector employment. The dramatic decline in the skill premium in Sweden is the result of an expanding public sector that has disproportionately hired unskilled labor.     

Employer-provided training,innovation and skills in post-Soviet countries

This paper analyzes the extent of employer-provided training in Armenia, Azerbaijan, Georgia and Ukraine and investigates its relationship with innovation, having international business contacts, use of computers at work, reported skills shortages and other firm characteristics. It contributes to the literature by examining different types of training – initial on-the-job learning, more formal in-house training and external training, which is provided by firms to two categories of workers – white- and blue-collar workers. After controlling for a range of firm characteristics, we find a positive link between technological innovation and intensity of training of all types provided to white-collar workers that points to the technology-skills complementarity. Furthermore, the level of computer use at work is a significant determinant of the incidence and intensity of external training provided to white-collar and blue-collar workers.     

剖线强度梯度变化的作物软硬变化区精确划分

[目的]软硬变化区的划分是进行遥感变化检测技术识别农作物的基础。为解决人工判读方法中存在人为主观因素影响以及自动判别和交互式判别方法对不同研究区的适用性问题,该文提出基于剖线梯度变化(Profile based Gradient Change Magnitude,PGCM)进行软硬变化区划分的方法。[方法]该研究选择破碎农业景观种植区域为研究区,计算拔节期Quick Bird影像和播种期模拟影像两个时相的变化强度,从作物地块内部向外绘制剖线,利用剖线强度的梯度变化确定硬变化区(Hard change region,HCR)、软变化区(Soft change region,SCR)和未变化区(Non change region,NCR)3者间的划分阈值。[结果]从识别结果来看,PGCM能够有效在地块边界处探测到软变化像元,进而确定HCR、SCR。像元分辨率在5~60 m不同尺度下,识别HCR区混入比例为11%~16%,混入比例随着分辨率下降而降低;NCR区混入比例为3%~4%,受分辨率尺度影响不大;SCR区识别比例为74%~86%,识别精度较高,识别结果与冬小麦空间分布结果保持一致。[结论]PGCM方法能够自动、便捷地确定阈值,摆脱人工判定的主观性,有效地划分出HCR、SCR和NCR 3个区域,为进一步HCR、SCR区内的作物识别提供基础。     

Similarities and Dissimilarities between Original Institutional Economics and New Institutional Economics

Original Institutional Economics and New Institutional Economics display several similarities. However, differences in methodology and normative stance are too big to reconcile both approaches. Both approaches may keep each other sharp.