Auxiliary Assumptions Research Articles

A new land rent theory for sustainable agriculture

The agri-food sector is a crucial element of “integrated order”, because its functioning depends on natural resources, especially on the land factor. There exists the crucial question of whether the land factor is still capable of generating economic rents which can be the determinants of comparative advantages. On the one hand, D. Ricardo’s land rents are vanishing, H. George’s rents are provoking financial crisis, and monetarists’ assumptions are proving inadequate; while on the other, the land factor is gaining new environmental applications, and there is still a hope that land rents have their origins in a real value. These premises entitle one to formulate the hypothesis that the productivity of capital in agriculture in Poland is increasing because of intrinsic values of agricultural land. That implies a need to rethink the neoclassical theories of land rent. The main objective of this article is to elaborate a framework of a new land rent theory and to test it. This is done by evaluating capital productivity in agriculture in Poland and comparing it with the land rent value derived from market prices of agricultural property. The falsification of the theory over a long period fails. Meanwhile, the auxiliary assumptions are verified, implying that the new concept of land rent may be a true one.

Bipartite Bell inequalities with three ternary-outcome measurements—from theory to experiments

We explore quantum nonlocality in one of the simplest bipartite scenarios. Several new facet-defining Bell inequalities for the scenario are obtained with their quantum violations analyzed in details. Surprisingly, all these inequalities involving only genuine ternary-outcome measurements can be violated maximally by some two-qubit entangled states, such as the maximally entangled two-qubit state. This gives further evidence that in analyzing the quantum violation of Bell inequalities, or in the application of the latter to device-independent quantum information processing tasks, the commonly held wisdom of equating the local Hilbert space dimension of the optimal state with the number of measurement outcomes is not necessarily justifiable. In addition, when restricted to the minimal qubit subspace, it can be shown that one of these Bell inequalities requires non-projective measurements to attain maximal quantum violation, thereby giving the first example of a facet-defining Bell inequality where a genuine positive-operator-valued measure is relevant. We experimentally demonstrate the quantum violation of this and two other Bell inequalities for this scenario using energy–time entangled photon pairs. Using the obtained measurement statistics, we demonstrate how characterization of the underlying resource in the spirit of device-independence, but supplemented with auxiliary assumptions, can be achieved. In particular, we discuss how one may get around the fact that, due to finite-size effects, raw measurement statistics typically violate the non-signaling condition.

Strongly seasonal Proterozoic glacial climate in low palaeolatitudes: Radically different climate system on the pre-Ediacaran Earth

Proterozoic (pre-Ediacaran) glaciations occurred under strongly seasonal climates near sea level in low palaeolatitudes. Metre-scale primary sand wedges in Cryogenian periglacial deposits are identical to those actively forming, through the infilling of seasonal (winter) thermal contraction-cracks in permafrost by windblown sand, in present-day polar regions with a mean monthly air temperature range of 40 °C and mean annual air temperatures of −20 °C or lower. Varve-like rhythmites with dropstones in Proterozoic glacial successions are consistent with an active seasonal freeze–thaw cycle. The seasonal (annual) oscillation of sea level recorded by tidal rhythmites in Cryogenian glacial successions indicates a significant seasonal cycle and extensive open seas. Palaeomagnetic data determined directly for Proterozoic glacial deposits and closely associated rocks indicate low palaeolatitudes: Cryogenian deposits in South Australia accumulated at ≤10°, most other Cryogenian deposits at <20° and Palaeoproterozoic deposits at <15° palaeolatitude. Palaeomagnetic data imply that the Proterozoic geomagnetic field approximated a geocentric axial dipole, hence palaeolatitudes represent geographic latitudes. The Cryogenian glacial environment included glacier-free, continental permafrost regions with ground frozen on a kyr time-scale, aeolian sand-sheets, extensive and long-lived open seas, and an active hydrological cycle. This palaeoenvironment conflicts with the ‘snowball Earth’ and ‘slushball Earth’ hypotheses, which cannot accommodate large seasonal changes of temperature near the equator. Consequently, their proponents have attempted to refute the evidence for strong seasonality by introducing Popperian ‘auxiliary assumptions’. However, non-actualistic arguments that the Cryogenian sand wedges indicate diurnal or weakly seasonal temperature changes are based on misunderstandings of periglacial processes. Modelling of a strongly seasonal climate for a frozen-over Earth is invalidated by the evidence for persistent open seas and glacier-free continental regions during Cryogenian glaciations, and gives a mean monthly air temperature range of only ≤10 °C for ≤10° latitude. By contrast, a strongly seasonal climate in low palaeolatitudes, based on the actualistic interpretation of cryogenic sand wedges and other structures, is consistent with a high obliquity of the ecliptic (>54°) during Proterozoic low-latitude glaciations, whereby the equator would be cooler than the poles, on average, and global seasonality would be greatly amplified.

Interpretation and the Hypothetico-Deductive Method: A Dilemma

Interpretation and the Hypothetico-Deductive Method: A Dilemma

Rational choice theory and social research

The paper is devoted to the analyses of methodological and metatheoretical problems of rational choice theory. The methodological challenge is associated with the questions: whether rational choice theory can be appropriately empirically tested and whether RCT allows researchers to derive interesting hypotheses with regard to substantive fields of application? The answers to these questions have important implications for the rational choice theory?s ambition to be appropriate basis for the implementation of social research. In this paper, allso, we analyse the following metatheoretical problems: how to deal with the apparent counterevidence that stems from applied fields of sociological research: Is it possible to provide explanations of this evidence within RCT by widening its core assumptions and thereby broadening the set of allowed auxiliary assumptions? Or does RCT have to be enriched (and if so, how?) by integrating concepts and mechanisms of other sociological approaches for it to remain a reasonable workhorse and starting point for sociological research?

Endogenous Firm Competition and the Cyclicality of Markups

The cyclicality of markups is crucial to understanding the propagation of shocks and the size of multipliers. I show that the degree of inertia in the response of output to shocks can reverse the cyclicality of markups within implicit collusion and customer-base models. In both classes of models, markups follow a forward looking law of motion in which they depend on firms' conditional expectations over stochastic discount rates and changes in output, implying that auxiliary assumptions that affect the inertia of output can potentially reverse cyclicality of markups in each of these models. I test this common law of motion with data for firms' expectations from New Zealand and find that firms' markup setting behavior is more consistent with implicit collusion models than customer base models. Calibrating an implicit collusion model to the U.S. data, I find that markups are procyclical if there is inertia in the response of output to shocks, as commonly found in the data.

Assessing financial stability: The Capital and Loss Assessment under Stress Scenarios (CLASS) model

Abstract The CLASS model is a top-down capital stress testing framework that uses public data, simple econometric models and auxiliary assumptions to project the effect of macroeconomic scenarios on U.S. banking firms. Through the lens of the model, we find that the total banking system capital shortfall under stressful macroeconomic conditions began to rise 4 years before the financial crisis, peaking in the fourth quarter of 2008. The capital gap has since fallen sharply, and is now significantly below pre-crisis levels. In the cross-section, banking firms estimated to be most sensitive to macroeconomic conditions also have higher capital ratios, consistent with a “precautionary” view of bank capital, though this behavior is evident only since the crisis. We interpret our results as evidence that the resiliency of the U.S. banking system has improved since the financial crisis, and also as an illustration of the value of stress testing as a macroprudential policy tool.

Analyzing Ordinal Data: Support for a Bayesian Approach

Ordinal data are often analyzed as if they were metric. After reviewing the literature on this practice, we present new evidence that analyzing ordinal data as metric is problematic. Using Monte Carlo simulations, we demonstrate that treating ordinal data as metric can yield low correct detection rates, distorted effect size estimates, and greatly inflated false alarm rates. Moreover, we demonstrate that the averaging of multiple ordinal items into a Likert scale does not solve these problems. We provide real examples of real data similar to the simulated data in the contexts of the difference of two groups and simple linear regression. To solve these problems we use an ordinal model with Bayesian estimation of parameters. The ordinal model does not yield low correct detection rates or high false alarm rates, and produces accurate effect sizes estimates and predicted response probabilities. Bayesian estimation of this ordinal model is straight forward, yields rich and accurate information, and has no need for auxiliary sampling assumptions. We conclude that ordinal data ought to be analyzed with ordinal models, and that Bayesian estimation is an excellent method for accomplishing that goal.

An argument for ψ-ontology in terms of protective measurements

The ontological model framework provides a rigorous approach to address the question of whether the quantum state is ontic or epistemic. When considering only conventional projective measurements, auxiliary assumptions are always needed to prove the reality of the quantum state in the framework. For example, the Pusey–Barrett–Rudolph theorem is based on an additional preparation independence assumption. In this paper, we give a new proof of ψ-ontology in terms of protective measurements in the ontological model framework. The proof does not rely on auxiliary assumptions, and it also applies to deterministic theories such as the de Broglie–Bohm theory. In addition, we give a simpler argument for ψ-ontology beyond the framework, which is based on protective measurements and a weaker criterion of reality. The argument may be also appealing for those people who favor an anti-realist view of quantum mechanics.

The alleged tradeoff between explanatory breadth and predictive power

It is almost a cliché that as theories gain in explanatory breadth, they lose in predictive power and as they gain in predictive power, they lose in explanatory breadth. We acknowledge that it is easy to generate examples in psychology that seem to exemplify the tradeoff between explanatory breadth and predictive power. Nevertheless, we believe that the tradeoff is far less clear-cut than psychology researchers have understood. Our argument is based on the necessity to make auxiliary assumptions when traversing the distance between non-observational terms in theories and observational terms in empirical hypotheses.

Why is Justice Regarded as so Important? Theoretical Considerations and an Empirical Test of a Fundamental Question

The paper investigates why justice is regarded as important in human groups and societies. Using the theory of social production functions (SPF) as a general model of action, the theoretical analysis focuses in a first step on the question of why individuals regard justice as valuable in social life. The theory of social production functions defines two fundamental human goals—physical and social well-being. The integration of justice concepts into a general model of human behavior demands to explain how justice enters an individual's social production functions. We predict a direct effect by just procedures that increases social well-being and an indirect effect by stability of auxiliary assumptions given by justice for the production of physical and social well-being. In a second step, the theoretical predictions are tested empirically. The analysis is based on a large dataset that contains 2,926 employees surveyed all over Germany. Using structural equation modeling, the empirical results support our hypotheses: Justice is more important for people who have deficits in physical and social well-being (H1). Moreover, these deficits are more important for justice in the public context than in the private context (H2). It can also be shown that people who work in cooperative situations in which they have to rely on others rate the importance of justice higher (H3). In conclusion, the importance of justice depends on the personal situation and the fulfillment of individual goals, and can be seen as functional on the individual level in ensuring an increase in benefits in cooperative interactions.

Path-integral method for the source apportionment of photochemical pollutants

Abstract. A new, path-integral method is presented for apportioning the concentrations of pollutants predicted by a photochemical model to emissions from different sources. A novel feature of the method is that it can apportion the difference in a species concentration between two simulations. For example, the anthropogenic ozone increment, which is the difference between a simulation with all emissions present and another simulation with only the background (e.g., biogenic) emissions included, can be allocated to the anthropogenic emission sources. The method is based on an existing, exact mathematical equation. This equation is applied to relate the concentration difference between simulations to line or path integrals of first-order sensitivity coefficients. The sensitivities describe the effects of changing the emissions and are accurately calculated by the decoupled direct method. The path represents a continuous variation of emissions between the two simulations, and each path can be viewed as a separate emission-control strategy. The method does not require auxiliary assumptions, e.g., whether ozone formation is limited by the availability of volatile organic compounds (VOCs) or nitrogen oxides (NOx), and can be used for all the species predicted by the model. A simplified configuration of the Comprehensive Air Quality Model with Extensions (CAMx) is used to evaluate the accuracy of different numerical integration procedures and the dependence of the source contributions on the path. A Gauss–Legendre formula using three or four points along the path gives good accuracy for apportioning the anthropogenic increments of ozone, nitrogen dioxide, formaldehyde, and nitric acid. Source contributions to these increments were obtained for paths representing proportional control of all anthropogenic emissions together, control of NOx emissions before VOC emissions, and control of VOC emissions before NOx emissions. There are similarities in the source contributions from the three paths but also differences due to the different chemical regimes resulting from the emission-control strategies.

Replication, falsification, and the crisis of confidence in social psychology.

The (latest) crisis in confidence in social psychology has generated much heated discussion about the importance of replication, including how it should be carried out as well as interpreted by scholars in the field. For example, what does it mean if a replication attempt “fails”—does it mean that the original results, or the theory that predicted them, have been falsified? And how should “failed” replications affect our belief in the validity of the original research? In this paper, we consider the replication debate from a historical and philosophical perspective, and provide a conceptual analysis of both replication and falsification as they pertain to this important discussion. Along the way, we highlight the importance of auxiliary assumptions (for both testing theories and attempting replications), and introduce a Bayesian framework for assessing “failed” replications in terms of how they should affect our confidence in original findings.

GENERAL INTEGRAL EQUATIONS OF MICROMECHANICS OF HETEROGENEOUS MATERIALS

One considers a linear composite medium, which consists of a homogeneous matrix containing either the periodic or random set of heterogeneities. An operator form of the general integral equation (GIE) is obtained for the general cases of local and nonlocal problems, static and wave motion phenomena for composite materials with periodic and random (statistically homogeneous and inhomogeneous, so-called graded) structures containing coated or uncoated inclusions of any shape and orientation with perfect and imperfect interfaces and subjected to any number of coupled or uncoupled, homogeneous or inhomogeneous external fields of different physical nature. The GIE, connecting the driving fields and fluxes in a point being considered and the fields in the surrounding points, are obtained for both the random and periodic fields of heterogeneities in the infinite media. The new GIE is presented in a general form of perturbations introduced by the heterogeneities and taking into account a possible imperfection of interface conditions. The mentioned perturbations can be found by any available numerical method which has advantages and disadvantages and it is crucial for the analyst to be aware of their range of applications. The method of obtaining of the GIE is based on a centering procedure of subtraction from both sides of a new initial integral equation their statistical averages obtained without any auxiliary assumptions such as the effective field hypothesis (EFH), which is implicitly exploited in the known centering methods. One proves the absolute convergence of the proposed GIEs which are presented in two equivalent forms for both the driving fields and fluxes. Some particular cases, asymptotic representations, and simplifications of proposed GIE are presented for the particular constitutive equations such as linear thermoelastic cases with the perfect and imperfect interfaces, conductivity problem, problems for piezoelectric and other coupled phenomena, composites with nonlocal elastic properties of constituents, and the wave propagation in composites with electromagnetic, optic, and mechanical responses.

Competing Gridlock Models and Status Quo Policies

Spatial theories of lawmaking predict that legislative productivity is increasing in the number of status quo policies that lie outside the gridlock interval, but because locations of status quo policies are difficult to measure, previous empirical tests of gridlock theories rely on an auxiliary assumption that the distribution of status quo points is fixed and uniform. This assumption is at odds with the theories being tested, as it ignores the history dependence of lawmaking. We provide an alternative method for testing competing theories by estimating structural models that explicitly account for temporal dependence in a theoretically consistent way. Our analysis suggests that legislative productivity depends both on parties and supermajority pivots, and we find patterns of productivity consistent with a weaker, contingent form of party influence than found in previous work. Parties appear to exert agenda power only on highly salient legislation rather than strongly influencing outcomes through voting pressure and party unity.

Natural Experiment Policy Evaluation: A Critique

We argue exogenous random treatment is insu¢ cient for valid inference regarding the sign and magnitude of causal eects in dynamic environments. In such settings, treatment responses must be understood as contingent upon the typically unmodeled policy generating process. With binary assignment, this results in quantitatively signi…cant attenuation bias. With more than two policy states, treatment responses can be biased downward, upward, or have the wrong sign. Further, it is not only generally invalid to extrapolate elasticities across policy processes, as argued by Lucas (1976), but also to extrapolate within the same policy process. We derive auxiliary assumptions beyond exogeneity for valid inference in dynamic settings. If all possible policy transitions are rare events, treatment responses approximate causal eects. However, reliance on rare events is overly-restrictive as the necessary and su¢ cient conditions for equality of treatment responses and causal eects is that policy variable changes have mean zero. If these conditions are not met, we show how treatment responses can nevertheless be corrected and mapped back to causal eects or extrapolated to forecast responses to future policy changes. � We thank Akitada Kasahara and Boris Radnaev for valuable research assistance and advice. We also thank seminar participants at LBS, Simon Fraser University, UBC, Koc University, and the Stanford Conference on Causality in the Social Sciences.

Signal detection and threshold modeling of confidence-rating ROCs: A critical test with minimal assumptions.

An ongoing discussion in the recognition-memory literature concerns the question of whether recognition judgments reflect a direct mapping of graded memory representations (a notion that is instantiated by signal detection theory) or whether they are mediated by a discrete-state representation with the possibility of complete information loss (a notion that is instantiated by threshold models). These 2 accounts are usually evaluated by comparing their (penalized) fits to receiver operating characteristic data, a procedure that is predicated on substantial auxiliary assumptions, which if violated can invalidate results. We show that the 2 accounts can be compared on the basis of critical tests that invoke only minimal assumptions. Using previously published receiver operating characteristic data, we show that confidence-rating judgments are consistent with a discrete-state account. (PsycINFO Database Record

Solution of general integral equations of micromechanics of heterogeneous materials

One considers a linear composite materials (CM), which consists of a homogeneous matrix containing a random set of heterogeneities. An operator form of solution of the general integral equation (GIE) for the general cases of local and nonlocal problems, static and wave motion phenomena for composite materials with random (statistically homogeneous and inhomogeneous, so-called graded) structures containing coated or uncoated inclusions of any shape and orientation with perfect and imperfect interfaces and subjected to any number of coupled or uncoupled, homogeneous or inhomogeneous external fields of different physical nature. The GIE, connecting the driving fields and fluxes in a point being considered and the fields in the surrounding points, are obtained for the random fields of heterogeneities in the infinite media. Estimations of the effective properties and both the first and second statistical moments of fields in the constituents of CMs are presented in a general form of perturbations introduced by the heterogeneities and taking into account a possible imperfection of interface conditions. The solution methods of GIEs are obtained without any auxiliary assumptions such as the effective field hypothesis (EFH), which is implicitly exploited in the known methods of micromechanics. Some particular cases, asymptotic representations, and simplifications of proposed methods are presented for the particular constitutive equations such as linear thermoelastic cases with the perfect and imperfect interfaces, conductivity problem, problems for piezoelectric and other coupled phenomena, composites with nonlocal elastic properties of constituents, and the wave propagation in composites with electromagnetic, optic and mechanical responses.

The Capital and Loss Assessment under Stress Scenarios (CLASS) Model

The CLASS model is a top-down capital stress testing framework that uses public data, simple econometric models and auxiliary assumptions to project the effect of macroeconomic scenarios on U.S. banking firms. Through the lens of the model, we find that the total banking system capital shortfall under stressful macroeconomic conditions began to rise four years before the financial crisis, peaking in the fourth quarter of 2008. The capital gap has since fallen sharply, and is now significantly below pre-crisis levels. In the cross-section, banking firms estimated to be most sensitive to macroeconomic conditions also have higher capital ratios, consistent with a “precautionary” view of bank capital, though this behavior is evident only since the crisis. We interpret our results as evidence that the resiliency of the U.S. banking system has improved since the financial crisis, and also as an illustration of the value of stress testing as a macroprudential policy tool.

Auxiliary Assumptions and Epistemic Ratios: Fun with Bayes

Although there have been many Bayesian analyses of the null hypothesis significance testing procedure, Bayesian thinking has not yet made strong inroads into theory testing (as opposed to hypothesis testing). We explain why this may be and how to introduce Bayesian thinking into theory testing. Bayesian evidence often comes in the form of empirical support for a hypothesis that was derived from a larger theory. We show that the probability of finding an empirical hypothesis to be true when a theory is true, and the probability of finding an empirical hypothesis to be true when a theory is false, are both fundamental in rigorous scientific knowledge accumulation. In turn, however, these conditional probabilities depend on the quality of the auxiliary assumptions that researchers use to traverse the distance from a more general theory to an empirical hypothesis. Therefore, we provide Bayesian analyses of theory testing that feature auxiliary assumptions. Our analyses implicate the importance of creativity o...