Tax Compliance: An Investigation Using Individual TCMP Data

In this paper, we analyze the tax compliance behavior of US taxpayers by using a 1979 data set that combines information from a random sample of individual tax returns each of which has been thoroughly audited, IRS administrative records, and sociodemographic data from the Census. We find evidence that both audits and tax code provisions affect compliance. However, the effects are significant for only the low and high income groups. Interestingly, previous research has shown that these groups also participate most actively in underground economic activities, the income from which is not reported on any tax returns. Our results for audits suggest that the "ripple" or general deterrent effect of audits may be many times larger than the direct revenue yield of audits for high income taxpayers. Our results for allowable subtractions from income imply that the 1986 Tax Reform Act changes to lower allowable subtractions may have procompliance effects.

A Structural Equation Model for Tax Compliance and Auditing

In this paper. we estimate a three equation model for taxpayers' reported income and tax liability and for the probability of an audit. Our work differs from previous studies in that our dependent variables in the compliance equations are taxpayer reports rather than a variable related to auditor estimates of noncompliance and in that we estimate a structural equation for audits. We find that audits stimulate compliance although the effect is not large and is not statistically significant for all groups. Audits are more effective at inducing accurate reporting of subtractions from income than of income. Reduced-form results suggest that IRS activities other than audits have significant compliance effects. Results for the sociodemographic variables are interesting and help to explain some seemingly incongruous findings in the literature. We find compliance to be higher, if anything. in areas with less educated and older taxpayers, a large proportion of households headed by females. and a mostly native born population.

A Normalized Tree Index for identification of correlated clinical parameters in microarray experiments

Martin C, Tauchen A, Becker A, Nattkemper TW. A Normalized Tree Index for identification of correlated clinical parameters in microarray data. BioData Mining. 2011;4(1): 2.BACKGROUND: Measurements on gene level are widely used to gain new insights in complex diseases e.g. cancer. A promising approach to understand basic biological mechanisms is to combine gene expression profiles and classical clinical parameters. However, the computation of a correlation coefficient between high-dimensional data and such parameters is not covered by traditional statistical methods. METHODS: We propose a novel index, the Normalized Tree Index (NTI), to compute a correlation coefficient between the clustering result of high-dimensional microarray data and nominal clinical parameters. The NTI detects correlations between hierarchically clustered microarray data and nominal clinical parameters (labels) and gives a measurement of significance in terms of an empiric p-value of the identified correlations. Therefore, the microarray data is clustered by hierarchical agglomerative clustering using standard settings. In a second step, the computed cluster tree is evaluated. For each label, a NTI is computed measuring the correlation between that label and the clustered microarray data. RESULTS: The NTI successfully identifies correlated clinical parameters at different levels of significance when applied on two real-world microarray breast cancer data sets. Some of the identified highly correlated labels confirm the actual state of knowledge whereas others help to identify new risk factors and provide a good basis to formulate new hypothesis. CONCLUSIONS: The NTI is a valuable tool in the domain of biomedical data analysis. It allows the identification of correlations between high-dimensional data and nominal labels, while at the same time a p-value measures the level of significance of the detected correlations

Economic Fluctuations and Diffusion

Stock price changes occur through transactions, just as diffusion in physical systems occurs through molecular collisions. We systematically explore this analogy and quantify the relation between trading activity - measured by the number of transactions $N_{\Delta t}$ - and the price change $G_{\Delta t}$, for a given stock, over a time interval $[t, t+\Delta t]$. To this end, we analyze a database documenting every transaction for 1000 US stocks over the two-year period 1994-1995. We find that price movements are equivalent to a complex variant of diffusion, where the diffusion coefficient fluctuates drastically in time. We relate the analog of the diffusion coefficient to two microscopic quantities: (i) the number of transactions $N_{\Delta t}$ in $\Delta t$, which is the analog of the number of collisions and (ii) the local variance $w^2_{\Delta t}$ of the price changes for all transactions in $\Delta t$, which is the analog of the local mean square displacement between collisions. We study the distributions of both $N_{\Delta t}$ and $w_{\Delta t}$, and find that they display power-law tails. Further, we find that $N_{\Delta t}$ displays long-range power-law correlations in time, whereas $w_{\Delta t}$ does not. Our results are consistent with the interpretation that the pronounced tails of the distribution of $G_{\Delta t} are due to$w_{\Delta t}$, and that the long-range correlations previously found for$| G_{\Delta t} |$are due to$N_{\Delta t}$.Comment: RevTex 2 column format. 6 pages, 36 references, 15 eps figure

Statistical Properties of Share Volume Traded in Financial Markets

We quantitatively investigate the ideas behind the often-expressed adage `it takes volume to move stock prices', and study the statistical properties of the number of shares traded $Q_{\Delta t}$ for a given stock in a fixed time interval $\Delta t$. We analyze transaction data for the largest 1000 stocks for the two-year period 1994-95, using a database that records every transaction for all securities in three major US stock markets. We find that the distribution $P(Q_{\Delta t})$ displays a power-law decay, and that the time correlations in $Q_{\Delta t}$ display long-range persistence. Further, we investigate the relation between $Q_{\Delta t}$ and the number of transactions $N_{\Delta t}$ in a time interval $\Delta t$, and find that the long-range correlations in $Q_{\Delta t}$ are largely due to those of $N_{\Delta t}$. Our results are consistent with the interpretation that the large equal-time correlation previously found between $Q_{\Delta t}$ and the absolute value of price change $| G_{\Delta t} |$ (related to volatility) are largely due to $N_{\Delta t}$.Comment: 4 pages, two-column format, four figure

Case Report A Rare Case of a 15-Year-Old Boy with Two Accessory Nipples: One in the Forearm and One in the Milk Line

A 15-year-old male presented for evaluation of a volar forearm mass that he noticed four years before. The mass was not painful and his main concern was cosmesis. The mass was two centimeters in diameter with a pinpoint central sinus and scant drainage. After excision, the pathology report noted pilosebaceous units and smooth muscle bundles, consistent with an accessory nipple. In addition, the patient had another accessory nipple in the "milk line" on his torso. While accessory nipples and breast tissue have been reported in numerous locations throughout the body, this is the first reported case of an accessory nipple on the forearm

A Practical, Accurate, Information Criterion for Nth Order Markov Processes

The recent increase in the breath of computational methodologies has been matched with a corresponding increase in the difficulty of comparing the relative explanatory power of models from different methodological lineages. In order to help address this problem a Markovian information criterion (MIC) is developed that is analogous to the Akaike information criterion (AIC) in its theoretical derivation and yet can be applied to any model able to generate simulated or predicted data, regardless of its methodology. Both the AIC and proposed MIC rely on the Kullback–Leibler (KL) distance between model predictions and real data as a measure of prediction accuracy. Instead of using the maximum likelihood approach like the AIC, the proposed MIC relies instead on the literal interpretation of the KL distance as the inefficiency of compressing real data using modelled probabilities, and therefore uses the output of a universal compression algorithm to obtain an estimate of the KL distance. Several Monte Carlo tests are carried out in order to (a) confirm the performance of the algorithm and (b) evaluate the ability of the MIC to identify the true data-generating process from a set of alternative models

The Economic Adjustment Program for Portugal : assessing welfare impact in a heterogeneous-agent framework

The sovereign debt crisis, triggered by the 2007-08 global financial cri- sis, has affected several European Union (EU) countries, leading to unprecedented financial assistance programs. In May 2011, the Portuguese Government set an agreement with the Troika (a supranational institution composed by the European Commission (EC), the European Central Bank (ECB) and the International Monetary Fund (IMF)), through which, in exchange for external help, the Portuguese author- ities committed to an Economic Adjustment Program (EAP). In order to assess the impacts of the EAP on welfare and, in particular, on inequality, this paper simulates the debt consolidation strategy proposed by the Troika using a general equilibrium model with heterogeneous agents. The model enables to explore the impacts of the fiscal adjustment on the endogenous cross-section distribution of income, wealth and welfare. Our results predict a positive net welfare gain, despite the existence of sig- nificant transition costs in terms of output losses and inequality, especially during the first years of implementation. Overall, the net positive welfare gains are biased towards the poorer, which means that the consolidation plan will be, in the end, equality-enhancing. These results reflect the instruments involved in the consolida- tion strategy: productive and unproductive expenditure cuts combined with a slight increase in social transfers. Furthermore, the simulation predicts a positive impact on the Portuguese net foreign asset (NFA) position. Assuming this prediction is correct, this strongly supports the motivation for the adoption of the Economic Adjustment Program which considers the large external indebtedness of Portugal as a central issue in the economic diagnosis.info:eu-repo/semantics/publishedVersio