Quantification of chlordesmethyldiazepam by liquid chromatography-tandem mass spectrometry: application to a cloxazolam bioequivalence study

A rapid, sensitive and specific LC-MS/MS method was developed and validated for quantifying chlordesmethyldiazepam (CDDZ or delorazepam), the active metabolite of cloxazolam, in human plasma. In the analytical assay, bromazepam (internal standard) and CDDZ were extracted using a liquid-liquid extraction (diethyl-ether/hexane, 80/20, v/v) procedure. The LC-MS/MS method on a RP-C18 column had an overall run time of 5.0 min and was linear (1/x weighted) over the range 0.5-50 ng/mL (R > 0.999). The between-run precision was 8.0% (1.5 ng/mL), 7.6% (9 ng/mL), 7.4% (40 ng/mL), and 10.9% at the low limit of quantification-LLOQ (0.500 ng/mL). The between-run accuracies were 0.1, -1.5, -2.7 and 8.7% for the above mentioned concentrations, respectively. All current bioanalytical method validation requirements (FDA and ANVISA) were achieved and it was applied to the bioequivalence study (Cloxazolam-test, Eurofarma Lab. Ltda and Olcadil (R)-reference, Novartis Biociencias S/A). The relative bioavailability between both formulations was assessed by calculating individual test/reference ratios for Cmax, AUClast and AUCO-inf. The pharmacokinetic profiles indicated bioequivalence since all ratios were as proposed by FDA and ANVISA. Copyright (C) 2009 John Wiley & Sons, Ltd.

Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

J.A. Ferreira Neto, E.C. Santos Junior, U. Fra Paleo, D. Miranda Barros, and M.C.O. Moreira. 2011. Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms. Cien. Inv. Agr. 38(2): 169-178. The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot`s productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.

Simultaneous analysis of five antidepressant drugs using direct injection of biofluids in a capillary restricted-access media-liquid chromatography-tandem mass spectrometry system

Direct analysis, with minimal sample pretreatment, of antidepressant drugs, fluoxetine, imipramine, desipramine, amitriptyline, and nortriptyline in biofluids was developed with a total run time of 8 min. The setup consists of two HPLC pumps, injection valve, capillary RAM-ADS-C18 pre-column and a capillary analytical C 18 column connected by means of a six-port valve in backflush mode. Detection was performed with ESI-MS/MS and only 1 mu m of sample was injected. Validation was adequately carried out using FLU-d(5) as internal standard. Calibration curves were constructed under a linear range of 1-250 ng mL(-1) in plasma, being the limit of quantification (LOQ), determined as 1 ng mL(-1), for all the analytes. With the described approach it was possible to reach a quantified mass sensitivity of 0.3 pg for each analyte (equivalent to 1.1-1.3 fmol), translating to a lower sample consumption (in the order of 103 less sample than using conventional methods). (C) 2008 Elsevier B.V. All rights reserved.

Trade effects of exchange rate fluctuations: Evidence from Sweden

An overview of the theoretical literature for the last two decades suggests that there is no clear-cut relationship one can pin down between exchange rate volatility and trade flows. Analytical results are based on specific assumptions and only hold in certain cases. Especially, the impact of exchange rate volatility on export and import activity investigated separately leads also to dissimilar conclusions among countries studied. The general presumption is that an increase in exchange rate volatility will have an adverse effect on trade flows and consequently, the overall heath of the world economy. However, neither theoretical models nor empirical studies provide us with a definitive answer, leaving obtained results highly ambiguous and inconsistent (Baum and Caglayan, 2006). We purposed to empirically investigate trade effects of exchange rate fluctuations in Sweden from the perspective of export and import in this research. The data comprises period from January 1993 to December 2006, where export and import volumes are considered from the point of their determinants, including exchange rate volatility, which has been measured through EGARCH model. The results for the case of Sweden show that short run dynamics of volatility negatively associated with both export and import, whereas considered from the case of previous period volatility it exhibits positive relationship. These results are consistent with the most findings of prior studies, where the relationship remained ambiguous.

Lifestyle and health status in a sample of Swedish women four years after pregnancy : a comparison of women with a history of normal pregnancy and women with a history of gestational diabetes mellitus

Background: Despite the recommendations to continue the regime of healthy food and physical activity (PA) postpartum for women with previous gestational diabetes mellitus (GDM), the scientific evidence reveals that these recommendations may not be complied to. This study compared lifestyle and health status in women whose pregnancy was complicated by GDM with women who had a normal pregnancy and delivery. Methods: The inclusion criteria were women with GDM (ICD-10: O24.4 A and O24.4B) and women with uncomplicated pregnancy and delivery in 2005 (ICD-10: O80.0). A random sample of women fulfilling the criteria (n = 882) were identified from the Swedish Medical Birth Register. A questionnaire was sent by mail to eligible women approximately four years after the pregnancy. A total of 444 women (50.8%) agreed to participate, 111 diagnosed with GDM in their pregnancy and 333 with normal pregnancy/ delivery. Results: Women with previous GDM were significantly older, reported higher body weight and less PA before the index pregnancy. No major differences between the groups were noticed regarding lifestyle at the follow-up. Overall, few participants fulfilled the national recommendations of PA and diet. At the follow-up, 19 participants had developed diabetes, all with previous GDM. Women with previous GDM reported significantly poorer self-rated health (SRH), higher level of sick-leave and more often using medication on regular basis. However, a history of GDM or having overt diabetes mellitus showed no association with poorer SRH in the multivariate analysis. Irregular eating habits, no regular PA, overweight/obesity, and regular use of medication were associated with poorer SRH in all participants. Conclusions: Suboptimal levels of PA, and fruit and vegetable consumption were found in a sample of women with a history of GDM as well as for women with normal pregnancy approximately four years after index pregnancy. Women with previous GDM seem to increase their PA after childbirth, but still they perform their PA at lower intensity than women with a history of normal pregnancy. Having GDM at index pregnancy or being diagnosed with overt diabetes mellitus at follow-up did not demonstrate associations with poorer SRH four years after delivery.

On the economic and fiscal effects of infrastructure investment in Brazil

This article studies the productive impact of infrastructure investment in Brazil. Public-capital expenditures in the country have decreased continuously over the last two decades, and this paper shows the significant impact this has had on infrastructure stocks. Cointegration analysis is used to investigate the long-run association between output and infrastructure, the results being then used to study the short-run dynamic of these variables. Whether in the short or long run, the productive impact of infrastructure was found to be relevant. Other group of simulations studies the impact of expanding capital expenditures through debt finance on debt to GDP ratio as well as on public cash áow and net worth.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian inflation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in different measures of forecasting accuracy are substantial, especially for short horizons.

Microeconomic instability and children's human capital accumulation: the effects of idiosyncratic shocks to father's income on child labor, school drop-outs and repetition rates in Brazil

This paper evaluates the long-run effects of economic instability. In particular, we study the impact of idiosyncratic shocks to father’s income on children’s human capital accumulation variables such as school drop-outs, repetition rates and domestic and non-domestic labor. Although, the problem of child labor in Brazil has declined greatly during the last decade, the number of children working is still substantial. The low levels of educational attainment in Brazil are also a main cause for concern. The large rotating panel data set used allows for the estimation of the impacts of changes in occupational and income status of fathers on changes in his child’s time allocation circumstances. The empirical analysis is restricted to families with fathers, mothers and at least one child between 10 and 15 years of age in the main Brazilian metropolitan areas during the 1982-1999 period. We perform logistic regressions controlling for child characteristics (gender, age, if he/she is behind in school for age), parents characteristics (grade attainment and income) and time and location variables. The main variables analyzed are dynamic proxies of impulses and responses, namely: shocks to household head’s income and unemployment status, on the one hand and child’s probability of dropping out of school, of repeating a grade and of start working, on the other. The findings suggest that father’s income has a significant positive correlation with child’s dropping out of school and of repeating a grade. The findings do not suggest a significant relationship between a father’s becoming unemployed and a child entering the non-domestic labor market. However, the results demonstrate a significant positive relationship between a father becoming unemployed and a child beginning to work in domestic labor. There was also a positive correlation between father becoming unemployed and a child dropping out and repeating a grade. Both gender and age were highly significant with boys and older children being more likely to work, drop-out and repeat grades.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian in ation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in di¤erent measures of forecasting accuracy are substantial, especially for short horizons.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

Financial disruption as a cost of sovereign default

This dissertation analyses quantitatively the costs of sovereign default for the economy, in a model where banks with long positions in government debt play a central role in the financial intermediation for private sector's investments and face financial frictions that limit their leverage ability. Calibration tries to resemble some features of the Eurozone, where discussions about bailout schemes and default risk have been central issues. Results show that the model captures one important cost of default pointed out by empirical and theoretical literature on debt crises, namely the fall in investment that follows haircut episodes, what can be explained by a worsening in banks' balance sheet conditions that limits credit for the private sector and raises their funding costs. The cost in terms of output decrease is though not significant enough to justify the existence of debt markets and the government incentives for debt repayment. Assuming that the government is able to alleviate its constrained budget by imposing a restructuring on debt repayment profile that allows it to cut taxes, our model generates an important difference for output path comparing lump-sum taxes and distortionary. For our calibration, quantitative results show that in terms of output and utility, it is possible that the effect on the labour supply response generated by tax cuts dominates investment drop caused by credit crunch on financial markets. We however abstract from default costs associated to the breaking of existing contracts, external sanctions and risk spillovers between countries, that might also be relevant in addition to financial disruption effects. Besides, there exist considerable trade-offs for short and long run path of economic variables related to government and banks' behaviour.

Implications of ernbodied technological change for development economics

Employing a embodied technologic change model in which the time decision of scrapping old vintages of capital and adopt newer one is endogenous we show that the elasticity of substitutions among capital and labor plays a key role in determining the optimum life span of capital. In particular, for the CD case the life span of capital does not depend on the relative price of it. The estimation of the model's long-run investment function shows, for a Panel data set consisting of 125 economies for 25 years, that the price elasticity of investment is lower than one; we rejected the CD specification. Our calibration for the US suggests 0.4 for the technical elasticity of substitution. In order to get a theoretical consistent concept of aggregate capital we derive the relative price profile for a shadow second-hand market for capital. The shape of the model's theoretical price curve reproduces the empírical estimation of it. \lVe plug the calibrate version of the long-run solution of the model to a cross-section of economies data set to get the implied TFP, that is, the part of the productivity which is not explained by the model. We show that the mo dei represent a good improvement, comparing to the standard neoc!assical growth model with CD production function and disembodied technical change, in accounting the world diversity in productivity. In addition the model describes the fact that a very poor economy can experience fast growth based on capital accumulation until the point of becoming a middle income economy; from this point on it has to rely on TFP increase in order to keep growing.