Asymmetrical state dependency from temporary septal area dysfunction in rats.

This study analyzes TV program content for viewers with respect to the following three properties: primary utility (intrinsic value by genre, cast, and so on), macro externality, such as the effect of others' past behavior (audience ratings), and state dependence, or the viewer's past actions that determine whether to watch the program. Focusing on the effects of macro externality and state-dependence on viewer behavior, the authors construct a hierarchical Bayesian model and derive an individual utility function. Applying their method to the choice of TV programs in Japan, they estimate the effects of macro externality and state dependence on an individual's viewing behavior, and illustrate the distribution of these effects. The authors find that macro externality has a strong overall effect on the total number of viewers and the state-dependence effect has a slightly positive effect. Moreover, comparing the attributes revealed that male viewers tend to show a lower effect of ratings and higher state dependence than females. They find that the older the viewers are, the higher the effect of state dependence. Further, using utility function data obtained by our estimation, they conduct a simulation to measure the dynamic effects of macro externality and state dependence.

In this paper we develop a general class of dynamic brand choice models, called Lightning Bolt (LB) models, which are consistent with the theory of random utility maximization of consumer choice behavior. The underlying random utility process is Markov, and the inter-temporal evolution of the (utility-maximizing) brand choice process is also Markov. The models permit parsimonious parameterizations of the random utility process in brand choices with the resulting switching probabilities being functionally related to explanatory variables. The model allows for structural state dependence (feedback), habit persistence (inertia), and unobserved heterogeneity. The theoretical development shows that several well known stochastic brand choice models can be deduced from random utility maximization theory. From a managerial perspective, the usefulness of the proposed model stems from its ability to separate out the effects of habits, state dependence and heterogeneity. Strong state dependence effects imply incentives for inducing trial of a brand (e.g., product sampling). In contrast with state dependence, a strong habit persistence effect may be indicative of buyer behavior where inducement of trial of a different brand may not be sufficient to maintain a (sustained) defection of the consumer from the habitually purchased brand to the trial brand. Failure to distinguish between these two effects has important implications. For example, a model that only accounts for state dependence effects would, in the presence of only habit persistence, incorrectly attribute it to state dependence. Based on this the manager could decide to embark on an expensive sampling program that might prove ineffective due to the absence of state dependence. It is also important to distinguish between the effects of unobserved heterogeneity and state dependence. In the absence of true state dependence, failing to account for unobservable variations across households (such as differences in price sensitivities), results in the temporally persistent unobservable elements showing up as state dependence in the model. Hence, a manager may incorrectly opt for sampling as the appropriate marketing action, whereas, a couponing or price promotion strategy should have been preferred. We estimate the model parameters using the AC Nielsen household scanner panel data set on catsup purchases. Further, we investigate empirical techniques for overcoming the “initial conditions” problem that affects many dynamic models of brand choice. Through simulation analysis using the estimated parameters, we show that the calculated profitability of a promotion must take into account the multi-period impact due to state dependence. Further, we demonstrate how ignoring heterogeneity can result in spurious state dependence, thereby making marketing tactics such as product sampling appear far more attractive than they actually are. Specifically, the model that accounts only for habit persistence and state dependence effects predicts a share increase of 2.4% points through sampling for one of the brands in the empirical analysis. Once the effects of unobserved heterogeneity are accounted for, however, this number drops precipitously to 0.3%. While even this low number might fulfill the objectives of the brand manager, it ensures that expectations are not eight times that number. It is important to note that this paper is a first attempt at analyzing the three fundamental dimensions of dynamic brand choice behavior. Our formulation represents a “reduced form” approach as opposed to a “structural” approach. Other limitations of the model include our focus on time-invariant choice sets. Extensions of the model to situations where choice sets vary over time are possible, but are difficult. Another limitation is the dependence on multivariate extreme value distributions. An alternative would be to use multivariate normal distributions, i.e., a probit-like structure which has certain useful properties. A comparison of the two approaches would be useful. Empirical extensions of the model to allow for higher-order processes and nested logit type model structures could also be fruitful. Explicitly incorporating variety-seeking behavior in the model would further enrich the theoretical framework proposed in this paper.

Since FY 2013, as a part of the Affordable Care Act (ACA) program, the Hospital Value-Based Purchasing (HVBP) program has adjusted Medicare’s payments to hospitals based on the total performance score of the hospital. First, the program reduces a portion of the hospital’s Medicare payments in a specific fiscal year, and then, by the end of the same fiscal year, the amount of the payment reductions will be awarded to the hospitals based on the total performance score; thus, the hospitals that do not receive the reward will lose the portion of money reduced by Medicare. In this research, we apply the theory of state dependence and use the dynamic random effect probit model to estimate this effect. The results show that the hospital payment adjustment dynamics have a very significant state dependence effect (0.341); this means that hospitals that received a reward in the previous year are 34.1% more likely to receive a reward this year than the ones that received a penalty in the previous year. Meanwhile, we also find that the state dependence effect varies significantly across hospitals with different ownership (proprietary/government owned/voluntary nonprofit), and the results show that voluntary nonprofit hospitals exhibit the largest effect of state dependence (0.370), while government-owned hospitals exhibit the lowest effect of state dependence (0.293), and proprietary hospitals are in the middle. Among the factors that influence the likelihood that a hospital receives a reward, we find that teaching hospitals with a large number of beds (>400) are less likely be rewarded; in terms of ownership, we find that voluntary nonprofit hospitals are more likely be rewarded; in terms of demographic factors, hospitals where the average household income are higher within the region are more likely be rewarded.

Probabilistic versus random-utility models of state dependence: an empirical comparison

Emerging experimental evidence suggests that both networks and their component neurons respond to similar inputs differently depending on the state of network activity. The network state is determined by the intrinsic dynamical structure of the network and may change as a function of neuromodulation, the balance or stochasticity of synaptic inputs to the network and the history of network activity. Much of the knowledge on state-dependent effects comes from comparisons of awake and sleep states of the mammalian brain. Yet, the mechanisms underlying these states are difficult to unravel. Several vertebrate and invertebrate studies have elucidated cellular and synaptic mechanisms of state-dependence resulting from neuromodulation, sensory input, and experience. Recent studies have combined modeling and experiments to examine the computational principles that emerge when network state is taken into account; these studies are highlighted in this article. We discuss these principles in a variety of systems (mammalian, crustacean, and mollusk) to demonstrate the unifying theme of state-dependence of network output.

No prior investigation has considered the effects of state dependence and unobserved heterogeneity on the relationship between regular physical activity (RPA) and latent health stock (LHS). Accounting for state dependence corrects the possible overestimation of the impact of socioeconomic factors. We estimated the degree of the state dependence of RPA and LHS among middle-aged Japanese workers. The 5 years’ longitudinal data used in this study were taken from the Longitudinal Survey of Middle and Elderly Persons. Individual heterogeneity was found for both RPA and LHS, and the dynamic random-effects probit model provided the best specification. A smoking habit, low educational attainment, longer work hours, and longer commuting time had negative effects on RPA participation. RPA had positive effects on LHS, taking into consideration the possibility of confounding with other lifestyle variables. The degree of state dependence of LHS was positive and significant. Increasing the intensity of RPA had positive effects on LHS and caused individuals with RPA to exhibit greater persistence of LHS compared to individuals without RPA. This result implies that policy interventions that promote RPA, such as smoking cessation, have lasting consequences. We concluded that smoking cessation is an important health policy to increase both the participation in RPA and LHS.

Life cycle employment and fertility across institutional environments

This study investigates discrepancies in offset choices between real-world and hypothetical scenarios by comparing stated preference (SP) and self-reported revealed preference (RP) data. Using multinomial logit (MNL) and mixed logit (MXL) models, key findings are: (1) preferences for offset contributions and prices are consistent across SP and RP, but differ in project types, locations, and certifications. (2) partial data enrichment harmonizes SP and RP within MNL models, outperforming full enrichment. (3) positive state dependence shows previous choices influence stated ones, with individual heterogeneity in MXL models. (4) incorporating unobserved heterogeneity and state-dependence effects is crucial when merging SP and RP.

We investigate the factors underlying poverty transitions in Nairobi’s slums focusing on whether differences in characteristics make people more prone to enter poverty and persist in, or whether past experience of poverty matters on future states. Understanding these issues is essential for the design of effective policy programs aimed at enhancing the lives of the poor. The paper uses an endogenous switching model, which accounts for initial conditions, non-random attrition, and unobserved heterogeneity.Estimations are based on a panel dataset from the Nairobi Demographic Surveillance System. Results indicate that true state dependence (TSD) constitutes the major factor driving poverty persistence. There are little heterogeneity effects. Even when household and individual observed characteristics differ notably, the TSD size remains very large. Active anti-poverty programs aimed at breaking the cycle of poverty constitute then the most appropriate policies for taking people out of poverty and preventing them to fall back in.

Estrous cycle contributes to state-dependent contextual fear in female rats

Benzodiazepine induced state-dependent learning: A correlative of abuse potential?

Drugs and human memory (part 2). Clinical, theoretical, and methodologic issues.

Normal subjects use the right insula and bilateral anterior temporal and prefrontal cortices to recognize the emotion expressed in a human face. Mood disorder subjects have a selective deficit in recognizing human facial emotion. Brain imaging studies show that they fail to activate the right insula to the same degree as controls, even when accurately assessing facial emotion. Many issues remain, however, including whether the facial emotion recognition errors in mood disorder subjects are state dependent or persist during normal mood states (and, thus, reflect a trait abnormality). To probe this issue, we repeatedly studied a male bipolar II patient's ability to recognize faces' emotional content. This patient made significantly more errors in facial emotion recognition during the depressed state. He also demonstrated a significant negative bias when he was depressed compared with nondepressed states. This case study demonstrates the state dependency of the defect in human facial emotion recognition.

Labor supply responses to tax changes are a core issue in public economics, reflected by numerous estimates from different methodological approaches. This dissertation contributes to the literature along two main avenues. First, I demonstrate how ex-ante simulations from a static discrete choice model can be validated ex-post by panel data methods estimating the elasticity of taxable earnings (Chapter 2). Second, I analyze the dynamics of labor supply responses to tax changes over time both with regards to panel data approaches (Chapter 3) and incorporated in a structural labor supply framework (Chapter 4). I use Norwegian register and survey data provided by Statistics Norway and focus on labor supply responses in working hours and wage earnings. In Chapter 2, I demonstrate how the standard elasticity of taxable income (ETI) methodology can be used to validate predictions from a structural labor supply model, by analyzing the Norwegian tax reform in 2006. To facilitate comparison, I use the discrete choice model to simulate the effects of the 2006 tax reform on hours of work, and use predicted income levels to obtain a comparable estimate for income elasticity with respect to the net-of-tax rate. In Chapter 3, I analyze the dynamics of earnings responses to tax changes by exploiting substantial exogenous variation in the two-tier surtax schedule for labor income over a period of 14 years (1995-2008). I adopt the dynamic panel data framework by Holmlund and Söderström (2011), and compare with estimates from the conventional static panel approach by Gruber and Saez (2002). I find that the long run responses to tax rate changes in labor supply are about twice as large as the short run responses due to a strong autoregressive effect in earnings. Supplementary conducted simulations suggest that up to 40 percent of the revenue loss due to tax rate cuts in the surtax schedule can be self- financed in the long run by inducing additional generated income. In Chapter 4, I examine the effect of state dependence to policy change responses over time within the framework of an intertemporal structural discrete choice model for women in couples. I allow for state dependence both in preferences and in the set of job opportunities. This causes sluggish labor supply responses to various changes in the wage rate and the tax schedule. Within the first year of a permanent policy change the simulation results suggest that about 50 percent of the full labor supply response can be expected, whereas 90 percent of the response is reached after about 4 years.

This paper analyzes the ownership dynamics of stocks and mutual funds, using representative household panel data, the Dutch CentER Savings Survey 1993–1998. A bivariate dynamic binary-choice model is introduced, allowing for interactions between the two types of assets. We find that unobserved heterogeneity and state dependence play a large role for both types of assets. The positive relation between ownership of one type in one period and the other type in the next period is explained by correlated unobserved heterogeneity. A negative state-dependence effect of lagged ownership of stocks on ownership of mutual funds is found, which can be explained by the costs of shifting funds across the two forms of stockholding.