CEO pay, shareholder returns, and accounting profits

We assess the impact on CEO pay (including salary, cash bonus, and benefits in kind) of changes in both accounting and shareholder returns in 99 British companies in the years 1972-89. After correcting for heterogeneity biases inherent in the standard specifications of the problem, we find a strong positive relationship between CEO pay and within-company changes in shareholder returns, and no statistically significant relationship between CEO pay and within-company changes in accounting returns. Differences between firms in long-term average profitability do appear to have a substantial effect on CEO pay, while differences between firms in shareholder returns add nothing to the within-firm pay dynamics.These findings call into question the rationale for explicitly share-based incentive schemes

Comparison between Dense L-Band and C-Band Synthetic Aperture Radar (SAR) Time Series for Crop Area Mapping over a NISAR Calibration-Validation Site

Crop area mapping is important for tracking agricultural production and supporting food security. Spaceborne approaches using synthetic aperture radar (SAR) now allow for mapping crop area at moderate spatial and temporal resolutions. Multi-frequency SAR data is highly useful for crop monitoring because backscatter response from vegetation canopies is wavelength dependent. This study evaluates the utility of C-band Sentinel-1B (Sentinel-1) and L-band ALOS-2 (PALSAR) data, collected during the 2019 growing season, for generating accurate active crop extent (crop vs. non-crop) classifications over an agricultural region in western Canada. Evaluations were performed against the Agriculture and Agri-Food Canada satellite-based Annual Cropland Inventory (ACI), an open data product that maps land cover across the extent of Canada’s agricultural land. Classifications were performed using the temporal coefficient of variation (CV) approach, where an optimal crop/non-crop delineating CV threshold (CVthr) is selected according to Youden’s J-statistic. Results show that crop area mapping agreed better with the ACI when using Sentinel-1 data (83.5%) compared to PALSAR (73.2%). Analysis of performance by crop reveals that PALSAR’s poorer performance can be attributed to soybean, urban, grassland, and pasture ACI classes. This study also compared CV values to in situ wet biomass data for canola and soybeans, showing that crops with lower biomass (soybean) had correspondingly lower CV value

In the dedicated pursuit of dedicated capital: restoring an indigenous investment ethic to British capitalism

Tony Blair’s landslide electoral victory on May 1 (New Labour Day?) presents the party in power with a rare, perhaps even unprecedented, opportunity to revitalise and modernise Britain’s ailing and antiquated manufacturing economy.* If it is to do so, it must remain true to its long-standing (indeed, historic) commitment to restore an indigenous investment ethic to British capitalism. In this paper we argue that this in turn requires that the party reject the very neo-liberal orthodoxies which it offered to the electorate as evidence of its competence, moderation and ‘modernisation’, which is has internalised, and which it apparently now views as circumscribing the parameters of the politically and economically possible

Correlates of therapist drift in psychological practice: A systematic review of therapist characteristics

Therapist drift refers to the tendency for psychologists to move away from the delivery of the evidence-based practices in which they are trained, even when resourced to implement them. When therapists do not provide, or only partially provide, empirically supported treatments their patients may receive interventions that are not effective, or that are harmful. The aim of the current study was to conduct a systematic review of the literature to ascertain the correlates of therapist drift in psychological practice, focusing on therapist characteristics. Relevant articles were identified through a comprehensive search of the literature. Sixty-six studies met the inclusion criteria and nine therapist characteristics that correlate with therapist drift were identified. These characteristics included: (1) therapist knowledge; (2) attitudes toward research; (3) therapist anxiety; (4) clinical experience; (5) therapist age; (6) theoretical orientation; (7) critical thinking; (8) personality traits; and (9) cultural competency. The interrelationships between these factors are explored and the clinical implications of results are discussed. Recommendations are made for future research

Comparison between Dense L-Band and C-Band Synthetic Aperture Radar (SAR) Time Series for Crop Area Mapping over a NISAR Calibration-Validation Site

Crop area mapping is important for tracking agricultural production and supporting food security. Spaceborne approaches using synthetic aperture radar (SAR) now allow for mapping crop area at moderate spatial and temporal resolutions. Multi-frequency SAR data is highly useful for crop monitoring because backscatter response from vegetation canopies is wavelength dependent. This study evaluates the utility of C-band Sentinel-1B (Sentinel-1) and L-band ALOS-2 (PALSAR) data, collected during the 2019 growing season, for generating accurate active crop extent (crop vs. non-crop) classifications over an agricultural region in western Canada. Evaluations were performed against the Agriculture and Agri-Food Canada satellite-based Annual Cropland Inventory (ACI), an open data product that maps land cover across the extent of Canada’s agricultural land. Classifications were performed using the temporal coefficient of variation (CV) approach, where an optimal crop/non-crop delineating CV threshold (CVthr) is selected according to Youden’s J-statistic. Results show that crop area mapping agreed better with the ACI when using Sentinel-1 data (83.5%) compared to PALSAR (73.2%). Analysis of performance by crop reveals that PALSAR’s poorer performance can be attributed to soybean, urban, grassland, and pasture ACI classes. This study also compared CV values to in situ wet biomass data for canola and soybeans, showing that crops with lower biomass (soybean) had correspondingly lower CV values

On the discrepancy between eddy covariance and lysimetry-based surface flux measurements under strongly advective conditions

Discrepancies can arise among surface flux measurements collected using disparate techniques due to differences in both the instrumentation and theoretical underpinnings of the different measurement methods. Using data collected primarily within a pair of irrigated cotton fields as a part of the 2008 Bushland Evapotranspiration and Remote Sensing Experiment (BEAREX08), flux measurements collected with two commonly-used methods, eddy covariance (EC) and lysimetry (LY), were compared and substantial differences were found. Daytime mean differences in the flux measurements from the two techniques could be in excess of 200Wm‒2 under strongly advective conditions. Three causes for this disparity were found: (i) the failure of the eddy covariance systems to fully balance the surface energy budget, (ii) flux divergence due to the local advection of warm, dry air over the irrigated cotton fields, and (iii) the failure of lysimeters to accurately represent the surface properties of the cotton fields as a whole. Regardless of the underlying cause, the discrepancy among the flux measurements underscores the difficulty in collecting these measurements under strongly advective conditions. It also raises awareness of the uncertainty associated with in situ micrometeorological measurements and the need for caution when using such data for model validation or as observational evidence to definitively support or refute scientific hypotheses

Synthetic Aperture Radar (SAR) image processing for operational space-based agriculture mapping

Few countries are using space-based Synthetic Aperture Radar (SAR) to operationally produce national-scale maps of their agricultural landscapes. For the past ten years, Canada has integrated C-band SAR with optical satellite data to map what crops are grown in every field, for the entire country. While the advantages of SAR are well understood, the barriers to its operational use include the lack of familiarity with SAR data by agricultural end-user agencies and the lack of a ‘blueprint’ on how to implement an operational SAR-based mapping system. This research reviewed order of operations for SAR data processing and how order choice affects processing time and classification outcomes. Additionally this research assessed the impact of speckle filtering by testing three filter types (adaptive, multi-temporal and multi-resolution) at varying window sizes for three study sites with different average field sizes. The Touzi multi-resolution filter achieved the highest overall classification accuracies for all three sites with varying window sizes, and with only a small (< 2%) difference in accuracy relative to the Gamma Maximum A Posteriori (MAP) adaptive filter which had similar window sizes across sites. As such, the assessment of order of operations for noise reduction and terrain correction was completed using the Gamma MAP adaptive filter. This research found there was no difference in classification accuracies regardless of whether noise reduction was applied before or after terrain correction. However, implementing the terrain correction as the first operation resulted in a 10 to 50% increase in processing time. This is an important consideration when designing and delivering operational systems, especially for large geographies like Canada where hundreds of SAR images are required. These findings will encourage country-wide, regional and global food monitoring initiatives to consider SAR sensors as an important source of data to operationally map agricultural production