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Reconstructability analysis (RA) is a method for detecting and analyzing the structure of multivariate categorical data. While Jones and his colleagues extended the original variable‐based formulation of RA to encompass models defined in terms of system states, their focus was the analysis and approximation of real‐valued functions. In this paper, we separate two ideas that Jones had merged together: the “g to k” transformation and state‐based modeling. We relate the idea of state‐based modeling to established variable‐based RA concepts and methods, including structure lattices, search strategies, metrics of model quality, and the statistical evaluation of model fit for analyses based on sample data. We also discuss the interpretation of state‐based modeling results for both neutral and directed systems, and address the practical question of how state‐based approaches can be used in conjunction with established variable‐based methods.

We take a state-stewardship view on corporate governance and executive compensation in economies with strong political involvement, where state-appointed managers act as responsible “stewards” rather than “agents” of the state.

We test this view on China and find that Chinese managers are remunerated not for maximizing equity value but for increasing the value of state-owned assets.

Managerial compensation depends on political connections and prestige, and on the firms’ contribution to political goals. These effects were attenuated since the market-oriented governance reform.

Economic reform without reforming the human resources policies at the executive level enables the autocratic state to exert political power on corporate decision making, so as to ensure that firms’ business activities fulfill the state’s political objectives.

As a powerful social elite, the state-steward managers in China have the same interests as the state (the government), namely extracting rents that should adhere to the nation (which stands for the society at large or the collective private citizens).

As China has been a communist country with a single ruling party for decades, the ideas of socialism still have a strong impact on how companies are run. The legitimacy of the elite’s privileged rights over private sectors is central to our question.

Chinese executive compensation stimulates not only the maximization of shareholder value but also the preservation of the state’s interests.

We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynamic Discrete Choice (DDC) structural models. These conditions can be used to estimate structural parameters in these models without having to solve for approximate value functions. This result extends to discrete choice models the GMM-Euler equation approach proposed by Hansen and Singleton (1982) for the estimation of dynamic continuous decision models. We first show that DDC models can be represented as models of continuous choice where the decision variable is a vector of choice probabilities. We then prove that the marginal conditions of optimality and the envelope conditions required to construct Euler equations are also satisfied in DDC models. The GMM estimation of these Euler equations avoids the curse of dimensionality associated to the computation of value functions and the explicit integration over the space of state variables. We present an empirical application and compare estimates using the GMM-Euler equations method with those from maximum likelihood and two-step methods.

This paper aims to show how a sociological description – a swarm analysis of the Nazi dictatorship – initially made with the means borrowed from George Spencer-Brown’s Calculus of Indications, can be transformed into a digital circuit and with which methods and tools of digital mathematics this digital circuit can be analyzed and described in its behavior. Thus, the paper also aims to contribute to a better understanding of Chapter 11 of “Laws of Form.”

The analysis uses methods of automata theory for finite, deterministic automata. Basic set operations of digital mathematics and special set operations of the Boolean Differential Calculus are used to calculate digital circuits. The software used is based on ternary logic, in which the binary Boolean logic of the elements {0, 1} is extended by the third element “Don’t care” to {0, 1, −}.

The paper confirms the method of transforming a form into a digital circuit derived from the comparative functional and structural analysis of the Modulator from Chapter 11 of “Laws of Form” and defines general rules for this transformation. It is shown how the indeterminacy of re-entrant forms can be resolved in the medium of time using the methods of automata theory. On this basis, a refined definition of the degree of a form is presented.

The paper shows the potential of interdisciplinary approaches between sociology and information technology and provides methods and tools of digital mathematics such as ternary logic, Boolean Differential Calculus and automata theory for application in sociology.

The idea that a bank's overall performance is influenced by the regional economy in which it operates is intuitive and broadly consistent with historical bank performance. Yet, micro-level research on the topic has borne mixed results, failing to find a consistent link between various measures of bank performance and regional economic variables. This chapter attempts to reconcile the intuition with the micro-level data by aggregating bank performance, as measured by nonperforming loans, up to the state level. This level of aggregation reduces the influence of idiosyncratic bank effects sufficiently so as to examine more clearly the influence of state-level economic variables. We show that regional variables, such as employment growth and changes in real estate prices, are not particularly useful for predicting changes in bank performance, but that coincident indicators developed to track a state's gross output are quite useful. We find that these coincident indicators have a statistically significant and economically important influence on state-level, aggregate bank performance. In addition, the coincident indicators potentially contribute to the out-of-sample forecasts of the relative riskiness of state-level bank portfolios, which should be of interest to bankers and bank supervisors.

The chapter offers complete details of the latest SGL version particularly suitable for dealing with large security systems and emerging crisis situations. It describes main types of constants representing information, physical matter or both and five very different and specific types of variables operating in fully distributed spaces and even being mobile themselves when serving spreading algorithms. Also given full repertoire of the language operations, called rules, which can be arbitrarily nested and carry different navigation, creation, processing, assignment, control, verification, context, exchange, transference, echoing, timing and other loads. The rules equally operate with local and remote values, process both, matter and distributed networked knowledge, and can express active graph-based patterns navigating, matching, conquering and changing distributed environments. Elementary programming examples in SGL are also provided.

This study examines a sharp decline of school attendance among white children in the Southern US after the Civil War. According to Census data, the school-attendance rate among whites in the Confederate states declined by almost half from 1860 to 1870, whereas the rate in Northern states was approximately stable. This shock left the South approximately three decades behind its antebellum trend. We account for little of this drop with household variables plausibly affected by the War. However, a select few county-level variables (notably the drop in wealth) explains around half of the decline, which suggests a systemic explanation. We adopt a model-based approach to decomposing the decline in schooling into demand versus supply factors. On the supply side, the region saw a decline in wealth and public resources, but we observe a stable relationship between time in school and literacy or adult occupation, which is not consistent with a contracting constraint on school quantity or quality. Nevertheless, further research is required to determine how much the contraction in school access affected attendance. On the demand-side, we present suggestive evidence of a decline in the return to school (measured by the relative wage of engineers to laborers). Relatedly, we see a “brain drain”: in longitudinally linked census samples, educated Southerners were more likely to migrate out of the South after the War.

The “baby-boom” generation is poised for retirement. Yet the American states exhibit sharp inequalities in the public support they provide for nursing facility long-term care for the elderly, a form of health care that few Americans can afford to purchase privately. Further, remarkable disparities exist, both within and among states, in the quality of nursing facility care. We describe cross-state variation in Medicaid support for and the quality of nursing facility care, offer regression models that provisionally explain the sources of these inequalities, comment on the social implications of these disparities and recommend a solution.

As an economic development strategy, entrepreneurship policies should target innovative activities – those which Schumpeter described as leading to new goods, production methods, markets, input sources, or new industries. However, popular entrepreneurship proxies, such as firm births (<500 employees) and sole proprietorships, capture multiple types of entrepreneurship which may have conflicting qualities. To address the need for more accurate measures of Schumpeterian activity, indices are constructed to specifically measure the relative amount of Schumpeterian activity among US states. The paper aims to discuss these issues.

Four composite indices of Schumpeterian activity are constructed using different methods to combine variables related to innovative activity into single indicator, since there is uncertainty about the weighting of dimensions: principal component analysis (PCA), factor analysis (FA), data envelopment analysis and equal weights. Robustness checks were used to compare state rankings across indices. These indices were also compared to common entrepreneurship proxies and real GDP to demonstrate and justify their measurement of Schumpeterian activity.

The results show that the Schumpeterian Activity Indices (SAIs) similarly rank states and measure phenomena different from the common proxies of entrepreneurship. Furthermore, these indices better predict GDP than the common proxies. Lastly, state rankings based upon the SAIs support previous research suggesting that innovation and agglomeration economies are interrelated.

The paper demonstrates a methodology for constructing a measure of innovative activity, which is necessary to develop and evaluate entrepreneurship policy for economic development.

Given the significant amount of public infrastructure spending and the widely expressed concern about the declining quality of the American public infrastructure system, research about the effectiveness of public infrastructure investment is especially timely and crucial. The study extends public service production theory and public choice theory to the public infrastructure field, and develops a realistic and full theoretical model of public highway production by taking state highway efficiency differences into account. The panel fixed-effects method is used to examine the effects of state highway finance on state highway infrastructure quality. This study finds that state highway maintenance spending plays a crucial role in improving state road and bridge quality. Moreover, highway efficiency elements matter for state highway infrastructure quality.