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Expectancy-disconfirmation has been the dominant paradigm to explain the formation of consumer satisfaction for over 40 years. Within this paradigm, it is possible for expectations to have opposing effects on consumer satisfaction depending on the underlying psychological processes presupposed. In general, assimilation processes predict positive effects, while contrast processes predict negative effects. A comprehensive assessment of the empirical evidence for these positions is missing. Hence, we provide a meta-analysis of expectancy-disconfirmation research, using 150 records ( N  = 58,597), to test the direct effects of perceived performance and performance expectations on consumer satisfaction, while also including disconfirmation as a mediator in each path (using meta-analytical path analysis). We found evidence for an overall positive relationship between expectations and consumer satisfaction ( r  = .29 [0.24, 0.34]) and no evidence supporting contrast effects. Moderator analyses revealed that the positive correlation between performance expectations and consumer satisfaction was significantly stronger for predictive (vs. normative) expectations, for services (vs. goods), and for cross-sectional (vs. longitudinal and experimental) studies. Furthermore, we found an unexpected downward publication bias, which suggests that the true correlation between disconfirmation and consumer satisfaction is higher than the (already high) estimate we found. We discuss how future research can empirically scrutinize popular practitioner views and promote the development of causal explanations, account for non-linear effects, and elucidate the anomalous publication bias found here. 

We investigate the impact of independent valuation specialists on the downward bias of pre-initial public offering employee stock option valuations. Undervalued stock price estimates underlying firms’ option grants produce option valuations that overstate earnings and provide employees with deep in the money options. We find independent stock price valuations are more likely for firms with a Big Four auditor and an audit committee accounting expert. Furthermore, valuations prepared by independent valuation specialists are less downward biased than those prepared internally. Cross-sectional results suggest the following. First, independent valuations have a stronger effect on reducing downward bias when the board is more independent, suggesting independent boards facilitate independent valuations. Second, independent valuations have a weaker effect on reducing downward bias when an accounting expert sits on the audit committee and when CEO equity ownership is greater, suggesting these factors offset the need for an independent valuation to reduce downward valuation bias.

The analytical, or harmonic, downward continuation of the external gravity potential into the topographic masses gives rise to a bias , which is called the analytical (downward) continuation (ADC) bias (Ågren in J Geod 78:314–332, 2004a) or the topographic bias (Sjöberg in J Geod, 2006). In Sjöberg (J Geod, 2006), a proof is presented that this bias is exactly equal to a simple two-term expression, which depends only on the topographic height and density in the evaluation point P . The expression is simple and inexpensive to evaluate. In this paper, we wish to question the validity of the expression given in Sjöberg (J Geod, 2006) for realistic terrains. The topographic bias is commonly defined as the difference between the true (internal) and the analytically downward continued external geopotential, evaluated at sea level. Typically both are evaluated as external or internal spherical harmonic (SH) expansions, which may however not always converge. If they do converge, they have been well known in the literature (e.g., Ågren (J Geod 78:314–332, 2004a), Wang (J Geod 71:70–82, 1997)) to produce a bias that contains additional terms over and beyond the simple expression. Below we analyze the additional terms that arise when applying the method to realistic terrains. Also, for realistic terrains, analytical downward continuation may not even be strictly possible. In practice , for discrete data sets, it is always possible, but then, an implicit smoothing of the terrain, or terrain potential, always takes place.

Improving access to productive employment is a key policy challenge, especially in low-income countries (LICs), where the only asset in abundance is labor. Building on ongoing research on earnings mobility, this study uses unusually rich longitudinal data from Ghana and Tanzania to identify engines of, and barriers to, earnings and earnings mobility. It examines the role of individual characteristics such as gender, age, and skills and characteristics of the job, but it also focuses on the role of job switches for example, moves into and out of self-employment. It zooms in particularly on the drivers of transitions between low-paying and high-paying jobs, and addresses questions such as whether being low paid is a transitory or permanent phenomenon, and whether it has a scarring effect on an individual's employment prospects. The extent to which earnings dynamics differ for women and young adults is also discussed in detail. The cross-country comparison of earnings dynamics and labor market transitions helps shed light on the institutional factors that promote labor market mobility and entrepreneurship. The report is organized as follows: chapter one gives introduction. Chapter two presents a brief review of related literature. Chapter three gives a descriptive overview of the labor markets in the two countries. Chapter four examines the determinants of earnings levels. Chapter five examines determinants of earnings growth. Chapter six focuses on low-pay and high-pay transitions and analyzes whether the experience of being in a low-paying job undermines an individual's future earnings prospects. Chapter seven discusses key policy implications.

Poor people derive most of their income from work; however, there is insufficient understanding of the role of employment and earnings as a linkage between growth and poverty reduction, especially in low income countries. With the objective of providing inputs into the policy discussion on how to enhance poverty reduction through increased employment and earnings for given growth levels, this study explores this linkage in the case of Madagascar using data from the national accounts and household surveys from the years 1999, 2001, and 2005, a period characterized among others by a short but severe crisis which started at the end of 2001 and the subsequent economic rebound. This report is part of a series of studies conducted in the context of the World Bank’s research framework aiming to improve the understanding of the linkages among growth, labor, and poverty reduction.

Does the method of divisor adjustment used for stocksplits in the Dow Jones Industrial Average (DJIA) cause a downward bias in the average’s level and does this method of adjustment cause increased volatility in the average? To investigate these issues, two averages are created using DJIA stocks. One average is adjusted for stock splits through adjustment in the divisor. This method is identical to the DJIA method of adjustment.The other average makes adjustment for stock splits by adjusting the stock value in the numerator. Relative to these two methods of adjustment for stock splits, there sults of the study demonstrate that there is no downward bias of the DJIA. Additionally, it is found that the method of divisor adjustment for stock splits does not increase the volatility of the average. When compared to the Standard and Poor’s Industrial Index, the DJIA does show downward bias.

We consider the topographic bias in gravimetric geoid determination when analytically downward continuing the disturbing potential from the Earth’s surface to sea level. The total bias is subdivided into those of the Bouguer shell or plate and the terrain. In this process, the potential of the Bouguer shell always has a downward continuation bias in the process, which increases with the square of the topographic height and typically exceeds 1–2 cm for elevations higher than 1 km. The main conclusion is that the terrain does not provide a potential bias except possibly for masses located inside a dome of height of about 0.4 times the height of the computation point, and base radius equal to the height of the computation point. This result implies that the potential of all terrain masses of arbitrary density located exterior to the Bouguer shell as well as those outside the dome are unbiasedly downward continued to sea level.

This study assesses a 40‐day 3.25‐km global simulation of the Simple Cloud‐Resolving E3SM Model (SCREAMv0) using high‐resolution ground‐based observations from the Atmospheric Radiation Measurement (ARM) Green Ocean Amazon (GoAmazon) field campaign. SCREAMv0 reasonably captures the diurnal timing of boundary layer clouds yet underestimates the boundary layer cloud fraction and mid‐level congestus. SCREAMv0 well replicates the precipitation diurnal cycle, however it exhibits biases in the precipitation cluster size distribution compared to scanning radar observations. Specifically, SCREAMv0 overproduces clusters smaller than 128 km, and does not form enough large clusters. Such biases suggest an inhibition of convective upscale growth, preventing isolated deep convective clusters from evolving into larger mesoscale systems. This model bias is partially attributed to the misrepresentation of land‐atmosphere coupling. This study highlights the potential use of high‐resolution ground‐based observations to diagnose convective processes in global storm resolving model simulations, identify key model deficiencies, and guide future process‐oriented model sensitivity tests and detailed analyses. Plain Language Summary This research examines how well a kilometer grid scale global atmospheric model—the Simple Cloud‐Resolving Energy Exascale Earth System Model (SCREAMv0)—performs in simulating clouds and rainfall over the Amazon rainforest region. The model was assessed by comparing to high‐resolution ground‐based observations from the Green Ocean Amazon field campaign supported by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program. The model struggles to produce enough middle‐level clouds. When comparing the simulated rainfall to radar observations, SCREAMv0 showed good performance on the diurnal pattern of rain rate, but tends to form too many small rain clusters while failing to create large ones. A possible contributor to these errors could be the inaccurate depiction of how the earth's surface and the atmosphere interact within the model. Overall, this study shows that using detailed DOE ARM data can help improve our understanding of clouds and rainfall in global storm resolving kilometer grid scale models. Key Points Convective processes in a global storm resolving model (SCREAMv0) are evaluated using ground‐based observations over a tropical rainforest SCREAMv0 captures the morning development of shallow convection and the early afternoon precipitation peak but lacks mid‐level congestus SCREAMv0 struggles to form large precipitation clusters greater than 128 km and produces smaller ones more often than observed

Surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR), its visible component, are key parameters needed for many land process models and terrestrial applications. Most existing DSR and PAR products were developed for climate studies and therefore have coarse spatial resolutions, which cannot satisfy the requirements of many applications. This paper introduces a new global high-resolution product of DSR (MCD18A1) and PAR (MCD18A2) over land surfaces using the MODIS data. The current version is Collection 6.0 at the spatial resolution of 5 km and two temporal resolutions (instantaneous and three-hour). A look-up table (LUT) based retrieval approach was chosen as the main operational algorithm so as to generate the products from the MODIS top-of-atmosphere (TOA) reflectance and other ancillary data sets. The new MCD18 products are archived and distributed via NASA’s Land Processes Distributed Active Archive Center (LP DAAC). The products have been validated based on one year of ground radiation measurements at 33 Baseline Surface Radiation Network (BSRN) and 25 AmeriFlux stations. The instantaneous DSR has a bias of −15.4 W/m2 and root mean square error (RMSE) of 101.0 W/m2, while the instantaneous PAR has a bias of −0.6 W/m2 and RMSE of 45.7 W/m2. RMSE of daily DSR is 32.3 W/m2, and that of the daily PAR is 13.1 W/m2. The accuracy of the new MODIS daily DSR data is higher than the GLASS product and lower than the CERES product, while the latter incorporates additional geostationary data with better capturing DSR diurnal variability. MCD18 products are currently under reprocessing and the new version (Collection 6.1) will provide improved spatial resolution (1 km) and accuracy.

Many climate models exhibit a dry and warm bias over the central United States during the summer months, including the Energy Exascale Earth System Model (E3SM) and its Multiscale Modeling Framework (MMF) configuration. Understanding the causes of this bias is important to shine a light on this common model error and reduce the uncertainty in future projections. In this study, we use E3SMv2 and E3SM-MMF to assess how parameterized and resolved convection affect temperature and precipitation biases over the Southern Great Plains site of the Atmospheric Radiation Measurement program. Both configurations overestimate near-surface temperature and underestimate precipitation at the ARM SGP site. The bias is associated with a lack of low-level clouds during days without precipitation and too much incoming solar radiation causing the surface to warm. Low-level cloud fraction in E3SM-MMF during the nonprecipitating days is lower in comparison to E3SMv2 and observation, consistent with the larger warm bias. We also find that the underestimated precipitation can be characterized as “too frequent, too weak” in E3SMv2 and “too rare, too intense” in E3SM-MMF. These deficiencies conspire to sustain the warm and dry bias over the central United States.