Relevant bibliographies by topics / Instrumental variable (IV) methods

Academic literature on the topic 'Instrumental variable (IV) methods'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Instrumental variable (IV) methods.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Instrumental variable (IV) methods"

1

Chesher, Andrew, and Adam M. Rosen. "What Do Instrumental Variable Models Deliver with Discrete Dependent Variables?" American Economic Review 103, no. 3 (May 1, 2013): 557–62. http://dx.doi.org/10.1257/aer.103.3.557.

Full text
Abstract:
We compare nonparametric instrumental variables (IV) models with linear models and 2SLS methods when dependent variables are discrete. A 2SLS method can deliver a consistent estimator of a Local Average Treatment Effect but is not informative about other treatment effect parameters. The IV models set identify a range of interesting structural and treatment effect parameters. We give set identification results for a counterfactual probability and an Average Treatment Effect in a IV binary threshold crossing model. We illustrate using data on female employment and family size (employed by Joshua Angrist and William Evans (1998)) and compare with their LATE estimates.
APA, Harvard, Vancouver, ISO, and other styles
2

Yuan, Junkun, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, and Lanfen Lin. "Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition." ACM Transactions on Knowledge Discovery from Data 16, no. 4 (August 31, 2022): 1–20. http://dx.doi.org/10.1145/3494568.

Full text
Abstract:
Instrumental variables (IVs), sources of treatment randomization that are conditionally independent of the outcome, play an important role in causal inference with unobserved confounders. However, the existing IV-based counterfactual prediction methods need well-predefined IVs, while it’s an art rather than science to find valid IVs in many real-world scenes. Moreover, the predefined hand-made IVs could be weak or erroneous by violating the conditions of valid IVs. These thorny facts hinder the application of the IV-based counterfactual prediction methods. In this article, we propose a novel Automatic Instrumental Variable decomposition (AutoIV) algorithm to automatically generate representations serving the role of IVs from observed variables (IV candidates). Specifically, we let the learned IV representations satisfy the relevance condition with the treatment and exclusion condition with the outcome via mutual information maximization and minimization constraints, respectively. We also learn confounder representations by encouraging them to be relevant to both the treatment and the outcome. The IV and confounder representations compete for the information with their constraints in an adversarial game, which allows us to get valid IV representations for IV-based counterfactual prediction. Extensive experiments demonstrate that our method generates valid IV representations for accurate IV-based counterfactual prediction.
APA, Harvard, Vancouver, ISO, and other styles
3

Chalak, Karim. "INSTRUMENTAL VARIABLES METHODS WITH HETEROGENEITY AND MISMEASURED INSTRUMENTS." Econometric Theory 33, no. 1 (February 15, 2016): 69–104. http://dx.doi.org/10.1017/s0266466615000390.

Full text
Abstract:
We study the consequences of substituting an error-laden proxy W for an instrument Z on the interpretation of Wald, local instrumental variable (LIV), and instrumental variable (IV) estimands in an ordered discrete choice structural system with heterogeneity. A proxy W need only satisfy an exclusion restriction and that the treatment and outcome are mean independent from W given Z. Unlike Z, W need not satisfy monotonicity and may, under particular specifications, fail exogeneity. For example, W could code Z with error, with missing observations, or coarsely. We show that Wald, LIV, and IV estimands using W identify weighted averages of local or marginal treatment effects (LATEs or MTEs). We study a necessary and sufficient condition for nonnegative weights. Further, we study a condition under which the Wald or LIV estimand using W identifies the same LATE or MTE that would have been recovered had Z been observed. For example, this holds for binary Z and therefore the Wald estimand using W identifies the same “average causal response,” or LATE for binary treatment, that would have been recovered using Z. Also, under this condition, LIV using W can be used to identify MTE and average treatment effects for e.g., the population, treated, and untreated.
APA, Harvard, Vancouver, ISO, and other styles
4

Banerjee, Souvik, and Anirban Basu. "Estimating Endogenous Treatment Effects Using Latent Factor Models with and without Instrumental Variables." Econometrics 9, no. 1 (March 17, 2021): 14. http://dx.doi.org/10.3390/econometrics9010014.

Full text
Abstract:
We provide evidence on the least biased ways to identify causal effects in situations where there are multiple outcomes that all depend on the same endogenous regressor and a reasonable but potentially contaminated instrumental variable that is available. Simulations provide suggestive evidence on the complementarity of instrumental variable (IV) and latent factor methods and how this complementarity depends on the number of outcome variables and the degree of contamination in the IV. We apply the causal inference methods to assess the impact of mental illness on work absenteeism and disability, using the National Comorbidity Survey Replication.
APA, Harvard, Vancouver, ISO, and other styles
5

Betz, Timm, Scott J. Cook, and Florian M. Hollenbach. "Spatial interdependence and instrumental variable models." Political Science Research and Methods 8, no. 4 (January 30, 2019): 646–61. http://dx.doi.org/10.1017/psrm.2018.61.

Full text
Abstract:
AbstractInstrumental variable (IV) methods are widely used to address endogeneity concerns. Yet, a specific kind of endogeneity – spatial interdependence – is regularly ignored. We show that ignoring spatial interdependence in the outcome results in asymptotically biased estimates even when instruments are randomly assigned. The extent of this bias increases when the instrument is also spatially clustered, as is the case for many widely used instruments: rainfall, natural disasters, economic shocks, and regionally- or globally-weighted averages. Because the biases due to spatial interdependence and predictor endogeneity can offset, addressing only one can increase the bias relative to ordinary least squares. We demonstrate the extent of these biases both analytically and via Monte Carlo simulation. Finally, we discuss a general estimation strategy – S-2SLS – that accounts for both outcome interdependence and predictor endogeneity, thereby recovering consistent estimates of predictor effects.
APA, Harvard, Vancouver, ISO, and other styles
6

Marshall, John. "Coarsening Bias: How Coarse Treatment Measurement Upwardly Biases Instrumental Variable Estimates." Political Analysis 24, no. 2 (2016): 157–71. http://dx.doi.org/10.1093/pan/mpw007.

Full text
Abstract:
Political scientists increasingly use instrumental variable (IV) methods, and must often choose between operationalizing their endogenous treatment variable as discrete or continuous. For theoretical and data availability reasons, researchers frequently coarsen treatments with multiple intensities (e.g., treating a continuous treatment as binary). I show how such coarsening can substantially upwardly bias IV estimates by subtly violating the exclusion restriction assumption, and demonstrate that the extent of this bias depends upon the first stage and underlying causal response function. However, standard IV methods using a treatment where multiple intensities are affected by the instrument–even when fine-grained measurement at every intensity is not possible–recover a consistent causal estimate without requiring a stronger exclusion restriction assumption. These analytical insights are illustrated in the context of identifying the long-run effect of high school education on voting Conservative in Great Britain. I demonstrate that coarsening years of schooling into an indicator for completing high school upwardly biases the IV estimate by a factor of three.
APA, Harvard, Vancouver, ISO, and other styles
7

Bishop, Kelly C., Sehba Husain-Krautter, Jonathan D. Ketcham, Nicolai V. Kuminoff, and Corbett Schimming. "Analyzing Individual-Level Secondary Data with Instrumental Variable Methods Is Useful for Studying the Effects of Air Pollution on Dementia." Journal of Alzheimer's Disease 79, no. 1 (January 5, 2021): 15–23. http://dx.doi.org/10.3233/jad-200497.

Full text
Abstract:
We hypothesize that analyzing individual-level secondary data with instrumental variable (IV) methods can advance knowledge of the long-term effects of air pollution on dementia. We discuss issues in measurement using secondary data and how IV estimation can overcome biases due to measurement error and unmeasured variables. We link air-quality data from the Environmental Protection Agency’s monitors with Medicare claims data to illustrate the use of secondary data to document associations. Additionally, we describe results from a previous study that uses an IV for pollution and finds that PM2.5’s effects on dementia are larger than non-causal associations.
APA, Harvard, Vancouver, ISO, and other styles
8

Faradiba, Faradiba. "Determination of Climate Factors in Flood and Drought Disaster in Indonesia using Instrumental Variable (IV) Methods." JURNAL ILMU FISIKA | UNIVERSITAS ANDALAS 13, no. 1 (February 28, 2021): 54–61. http://dx.doi.org/10.25077/jif.13.1.54-61.2021.

Full text
Abstract:
Located in the Southeast Asia region, Indonesia has rainy and dry seasons. In the rainy and dry seasons that occur in Indonesia, often causes many problems in various business sectors and community activities, including floods and droughts. It is known that the disaster will have an impact on material and non-material losses. This study uses climate data and disaster data at the village level to determine the effect of rainfall on disasters. This study uses the instrumental variable method because the model has endogeneity problems. The study results concluded that increased rainfall had a positive impact on flood disasters with a coefficient of 0.003038. Simultaneously, rainfall also impacted drought with a coefficient of -0.000377. Variables in the regression model that are formed can explain 1.74 percent of the flood disaster and 0.59 percent of the drought disaster. These results indicate that most of the other variables can influence flooding and drought. Through this research, it is known that rainfall for floods and droughts is quite significant. Therefore, government and community efforts are needed to anticipate similar disasters.
APA, Harvard, Vancouver, ISO, and other styles
9

Saini, Vikram, and Lillie Dewan. "Instrument variable method based on nonlinear transformed instruments for Hammerstein system identification." Journal of Vibration and Control 24, no. 13 (February 22, 2017): 2802–14. http://dx.doi.org/10.1177/1077546317694770.

Full text
Abstract:
An extended instrumental variable (EIV) method is considered for the stochastic Hammerstein system (ARMAX and general model structure). The EIV method provides consistent parameter estimates by eliminating noise-induced bias in the least square (LS) method. To estimate the parameters, the Hammerstein model is formulated using the bilinear parameterization. The bilinear model is identified by introducing the nonlinear instrumental variables obtained from transformed delayed outputs using nonlinear mapping and polynomial basis of delayed inputs. These instruments are analyzed in full generality by computing the bounds on expected relationship between instruments and noise for the general noise disturbance structure. Then, a specific case with hyperbolic tangent (tanh) transformation is considered. Comparative performance analysis of the proposed IV method with the existing IV method, the data filtering-based LS methods, and the extended LS method shows improvement in the statistical properties of parameters estimates.
APA, Harvard, Vancouver, ISO, and other styles
10

Mogstad, Magne, and Alexander Torgovitsky. "Identification and Extrapolation of Causal Effects with Instrumental Variables." Annual Review of Economics 10, no. 1 (August 2, 2018): 577–613. http://dx.doi.org/10.1146/annurev-economics-101617-041813.

Full text
Abstract:
Instrumental variables (IV) are widely used in economics to address selection on unobservables. Standard IV methods produce estimates of causal effects that are specific to individuals whose behavior can be manipulated by the instrument at hand. In many cases, these individuals are not the same as those who would be induced to treatment by an intervention or policy of interest to the researcher. The average causal effect for the two groups can differ significantly if the effect of the treatment varies systematically with unobserved factors that are correlated with treatment choice. We review the implications of this type of unobserved heterogeneity for the interpretation of standard IV methods and for their relevance to policy evaluation. We argue that making inferences about policy-relevant parameters typically requires extrapolating from the individuals affected by the instrument to the individuals who would be induced to treatment by the policy under consideration. We discuss a variety of alternatives to standard IV methods that can be used to rigorously perform this extrapolation. We show that many of these approaches can be nested as special cases of a general framework that embraces the possibility of partial identification.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Instrumental variable (IV) methods"

1

Abadie, Alberto 1968. "Semiparametric instrumental variable methods for causal response models." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/38857.

Full text
Abstract:
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Economics, c1999.
Includes bibliographical references.
This dissertation proposes new instrumental variable methods to identify, estimate and test for causal effects of endogenous treatments. These new methods are distinguished by the combination of nonparametric identifying assumptions and semiparametric estimators that provide a parsimoniuous summary of the results. The thesis consists of three essays presented in the form of chapters. The first chapter shows how to estimate linear and nonlinear causal response functions with covariates under weak (instrumental variable) identification restrictions. The second chapter (co-authored with Joshua Angrist and Guido Imbens) applies the identification results of the first chapter to estimate quantile causal response functions, so we can study the effect of the treatment on different parts of the distribution of the outcome variable. The third chapter of this dissertation looks again at distributional effects but focusing directly on the cumulative distribution functions of the potential outcomes with and without the treatment.
by Alberto Abadie.
Ph.D.
APA, Harvard, Vancouver, ISO, and other styles
2

Winkelried, Diego. "Methods to improve the finite sample behaviour of instrumental variable estimators." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609238.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Arnarsdottir, Joanna, and Kristina Hansson. "Can Export Diversification Save sub-Saharan Africa from Extreme Weather? : An instrumental variable approach." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-434996.

Full text
Abstract:
Growth and development in the context of climate change and environmental challengesare issues of increasing importance in the economic debate. With higher levels of greenhousegases in the atmosphere, droughts and other forms of extreme weather are expected to increasein frequency. Some of the worst affected are people living in sub-Saharan African countries. However, there are literature showing that countries who diversify their production becomesmore resilient against negative shocks. This study aims to determine the relationship betweenprecipitation anomalies and GDP per capita growth under different levels of concentrationof the export portfolio, in order to understand what kind of diversification reduces economicrisks connected to precipitation. Precipitation anomalies, such as abnormally heavy rainfallor droughts, is seen as a good measurement for climate change, and can thus be treated aseconomic shocks. We are using data on export product shares and monthly precipitation todetermine whether the level of sectoral diversification in exports affects the influence precipitation anomalies have on GDP per capita growth. The effects are estimated using a two-stageleast squares model, only targeting countries in SSA for our estimations. The results show thatpositive weather anomalies correlate with lower levels of GDP per capita growth. But the samenegative trend cannot be seen for negative precipitation anomalies. The results also show thatthe level of diversification within exports does not have any significant effect on the influencethat precipitation anomalies have on GDP per capita growth.
APA, Harvard, Vancouver, ISO, and other styles
4

Goldsmith, Kimberley. "Instrumental variable and longitudinal structural equation modelling methods for causal mediation : the PACE trial of treatments for chronic fatigue syndrome." Thesis, King's College London (University of London), 2014. https://kclpure.kcl.ac.uk/portal/en/theses/instrumental-variable-and-longitudinal-structural-equation-modelling-methods-for-causal-mediation-the-pace-trial-of-treatments-for-chronic-fatigue-syndrome(413e5fb0-03b9-40bc-b993-0465b1bcbdee).html.

Full text
Abstract:
Background: Understanding complex psychological treatment mechanisms is important in order to refine and improve treatment. Mechanistic theories can be evaluated using mediation analysis methods. The Pacing, Graded Activity, and Cognitive Behaviour Therapy: A Randomised Evaluation (PACE) trial studied complex therapies for the treatment of chronic fatigue syndrome. The aim of the project was to study different mediation analysis methods using PACE trial data, and to make trial design recommendations based upon the findings. Methods: PACE trial data were described using summary statistics and correlation analyses. Mediation estimates were derived using: the product of coefficients approach, instrumental variable (IV) methods with randomisation by baseline variables interactions as IVs, and dual process longitudinal structural equation models (SEM). Monte Carlo simulation studies were done to further explore the behaviour of IV estimators and to examine aspects of the SEM. Results: Cognitive and behavioural measures were mediators of the cognitive behavioural and graded exercise therapies in PACE. Results were robust when accounting for correlated measurement error and different SEM structures. Randomisation by baseline IVs were weak, giving imprecise and sometimes extreme estimates, leaving their utility unclear. A flexible version of a latent change SEM with contemporaneous mediation effects and contemporaneous correlated measurement errors was the most appropriate longitudinal model. Conclusions: IV methods using interaction IVs are unlikely to be useful; designs with randomised IV might be more suitable. Longitudinal SEM for mediation in clinical trials seems a promising approach. Mediation estimates from SEM were generally robust when allowing for correlated measurement error and for different model classes. Mediation analysis in trials should be longitudinal and should consider the number and timing of measures at the design stage. Using appropriate methods for studying mediation in trials will help clarify treatment mechanisms of action and allow for their refinement, which would maximize the information gained from trials and benefit patients.
APA, Harvard, Vancouver, ISO, and other styles
5

Lahlou, Mehdi, and Sebastian Sandstedt. "Where There’s Smoke, There’s Fire : An Analysis of the Riksbank’s Interest Setting Policy." Thesis, Stockholms universitet, Nationalekonomiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-143163.

Full text
Abstract:
We analyse the Swedish central bank, the Riksbank’s, interest setting policy in a Taylor rule framework. In particular, we examine whether or not the Riksbank has reacted to fluctuations in asset prices during the period 1995:Q1 to 2016:Q2. This is done by estimating a forward-looking Taylor rule with interest rate smoothing, augmented with stock prices, house prices and the real exchange rate, using IV GMM. In general, we find that the Riksbank’s interest setting policy is well described by a forward-looking Taylor rule with interest rate smoothing and that the use of factors as instruments, derived from a PCA, serves to alleviate the weak-identification problem that tend to plague GMM. Moreover, apart from finding evidence that the Riksbank exhibit a substantial degree of policy rate inertia and has acted so as to stabilize inflation and the real economy, we also find evidence that the Riksbank has been reacting to fluctuations in stock prices, house prices, and the real exchange rate.
APA, Harvard, Vancouver, ISO, and other styles
6

Vilela, Lucas Pimentel. "Wald tests for IV regression with weak instruments." reponame:Repositório Institucional do FGV, 2013. http://hdl.handle.net/10438/11222.

Full text
Abstract:
Submitted by Lucas Pimentel Vilela (lvilela@fgvmail.br) on 2013-10-07T17:22:14Z No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5)
Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2013-10-08T21:33:30Z (GMT) No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5)
Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2013-10-14T14:44:28Z (GMT) No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5)
Made available in DSpace on 2013-10-14T14:45:02Z (GMT). No. of bitstreams: 2 Dissertação Final.pdf: 665295 bytes, checksum: b54a14202e41e19e863a73328cfb2123 (MD5) Supplement.pdf: 2259071 bytes, checksum: 19718d483c50f35f3878c81521b0acf9 (MD5) Previous issue date: 2013-09-17
This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).
Esta dissertação trata do problema de inferência na presença de identificação fraca em modelos de regresso com variáveis instrumentais. Mais especificamente em testes de hipóteses com relação ao parâmetro da variável endógena quando os instrumentos são fracos. O principal foco é nos testes condicionais unilaterais baseados nas estatísticas de razão de máxima verossimilhança, score e Wald. Resultados teóricos e numéricos mostram que o teste t condicional unilateral baseado no estimador de mínimos quadrados em dois estágios tem uma boa performance mesmo na presença de instrumentos fracamente correlacionados com a variável endógena. A abordagem condicional corrige uniformemente o tamanho do teste t e quando a estatística F populacional é tão pequena quanto dois, o poder do teste é próximo ao power envelope tanto de testes similares quanto de não similares. Tal resultado é surpreendente visto a má performance dos testes t’s condicionais bilaterais relatada em (6, Andrews, Moreira and Stock (2007)). Dado esse resultado aparentemente contra intuitivo, apresentamos novos testes t’s condicionals bilaterais que são aproximadamente não viesados e performam, em alguns casos, tão bem quanto o teste condicional baseado na estatística de razão de verossimilhança de ( 19 , Moreira (2003)).
APA, Harvard, Vancouver, ISO, and other styles
7

Brunot, Mathieu. "Identification of rigid industrial robots - A system identification perspective." Phd thesis, Toulouse, INPT, 2017. http://oatao.univ-toulouse.fr/20776/1/BRUNOT_Mathieu_20776.pdf.

Full text
Abstract:
In modern manufacturing, industrial robots are essential components that allow saving cost, increase quality and productivity for instance. To achieve such goals, high accuracy and speed are simultaneously required. The design of control laws compliant with such requirements demands high-fidelity mathematical models of those robots. For this purpose, dynamic models are built from experimental data. The main objective of this thesis is thus to provide robotic engineers with automatic tools for identifying dynamic models of industrial robot arms. To achieve this aim, a comparative analysis of the existing methods dealing with robot identification is made. That allows discerning the advantages and the limitations of each method. From those observations, contributions are presented on three axes. First, the study focuses on the estimation of the joint velocities and accelerations from the measured position, which is required for the model construction. The usual method is based on a home-made prefiltering process that needs a reliable knowledge of the system’s bandwidths, whereas the system is still unknown. To overcome this dilemma, we propose a method able to estimate the joint derivatives automatically, without any setting from the user. The second axis is dedicated to the identification of the controller. For the vast majority of the method its knowledge is indeed required. Unfortunately, for copyright reasons, that is not always available to the user. To deal with this issue, two methods are suggested. Their basic philosophy is to identify the control law in a first step before identifying the dynamic model of the robot in a second one. The first method consists in identifying the control law in a parametric way, whereas the second one relies on a non-parametric identification. Finally, the third axis deals with the home-made setting of the decimate filter. The identification of the noise filter is introduced similarly to methods developed in the system identification community. This allows estimating automatically the dynamic parameters with low covariance and it brings some information about the noise circulation through the closed-loop system. All the proposed methodologies are validated on an industrial robot with 6 degrees of freedom. Perspectives are outlined for future developments on robotic systems identification and other complex problems.
APA, Harvard, Vancouver, ISO, and other styles
8

Kluberg, Sheryl. "Evaluating South African policies for linkage to and retention in HIV care using quasi-experimental methods." Thesis, 2017. https://hdl.handle.net/2144/27163.

Full text
Abstract:
South Africa has the largest HIV-infected population in the world, with 2015 estimates of 7 million people living with HIV and 180,000 AIDS-related deaths. The South African government began scale-up of a public-sector HIV care and treatment program in 2004, and by the end of 2015, 3.4 million HIV-infected individuals were on antiretroviral therapy (ART). When scale-up began in South Africa, ART was only available to HIV-infected individuals with CD4 counts ≤200 cells/µL or WHO clinical stage 4 disease. In 2010, treatment was extended to patients who were pregnant or who had tuberculosis and a CD4 ≤350 cells/µL, and in 2011, eligibility was extended to all patients with CD4 ≤350 cells/µL. In 2013 patients with WHO clinical stage 3 disease became eligible. In 2015, the eligibility threshold was increased to CD4 ≤500 cells/µL, and in 2016, the South African National Department of Health announced that the country would implement a “test and treat” strategy, offering free ART to all HIV-infected individuals, regardless of CD4 count. This dissertation examines the effectiveness of several expansions and modifications to South Africa’s treatment program. In study 1, we investigated whether the 2011 extension of HIV treatment to patients with CD4 counts ≤350 cells/µL successfully increased the number of newly-eligible patients on treatment (those with CD4 counts between 201–350 cells/µL) without crowding out previously-eligible patients with more severe disease (CD4 counts ≤200 cells/µL), focusing on a network of rural clinics in KwaZulu-Natal. We found encouraging results, with newly-eligible patients (CD4 201–350) initiating treatment at a greater frequency (73.0 additional patients per month; 95% CI: 42.1; 103.9) and 47% faster than before (95% CI: 19%; 82%), while previously eligible patients (CD4 ≤200) experienced no decline in the number of patients initiating treatment or the speed of treatment uptake. In study 2, we evaluated whether the introduction of a single-pill fixed-dose combination (FDC) treatment for ART initiators in South Africa had an impact on attrition from care compared to the previously-recommended multiple-pill regimen. We focused on an urban clinic in Johannesburg, using four different clinic attendance measures to define attrition (generally a combined measure of loss to follow-up and mortality). An intention-to-treat analysis revealed an estimated 11.3 percentage point decrease in attrition (95% CI: -22.0; -0.6) associated with the policy change, while a regression discontinuity analysis estimated an 18.0 percentage point drop in attrition (95% CI: -33.6; -2.4) associated with single-pill FDC treatment relative to multiple pills, controlling for unmeasured confounding. In study 3, we used stratified instrumental variable analysis to examine whether the effect of FDCs on attrition varied across subsets of the patient population in the same Johannesburg clinic we evaluated in study 2. We saw larger effects among women (RD -0.25; 95% CI: -0.42; -0.09), non-anemic patients (RD -0.24; 95% CI: -0.41; -0.08), patients with early-stage (as opposed to advanced) clinical disease (RD -0.20; 95% CI: -0.32; -0.07), and those with high CD4 counts (for CD4 ≥350 cells/µL, RD -0.58; 95% CI: -1.58; 0.42). These results suggest that healthier patients saw the greatest improvement in retention in care following the switch from multiple-pill to single-pill regimens. In an era where the healthiest HIV-infected patients are now being targeted for ART treatment, FDCs can play a large role in preventing attrition from care. These three studies depict an HIV program that has successfully grown to treat increasing numbers of patients using up-to-date strategies of care. Given the immense scale and cost of South Africa’s HIV treatment program, it is important to continue to monitor its effectiveness, especially as it introduces new treatments and strategies and adapts to the changing epidemic.
APA, Harvard, Vancouver, ISO, and other styles
9

Srna, Jan. "Závislost načasování odchodu do důchodu na existenci vnoučat: evidence s využitím dat SHARE." Master's thesis, 2021. http://www.nusl.cz/ntk/nusl-447175.

Full text
Abstract:
This thesis examines the role of grandchildren's existence in the retirement timing decision- making process of grandparents. Previous literature has focused mostly on other aspects of retirement and potential causes that can affect its timing. Using the Two-Stage least squares estimation on the SHARE dataset, representing 17 European countries and Israel, we estimate the desired effect with respect to various data limitations (age groups, gender, child existence). Residential proximity is used as the instrument for estimation. Having at least one grandchild yields a statistically significant result that increases on average the likelihood of retirement by 19% when compared to a non-grandparent while holding other factors constant. As a secondary outcome, the estimated effect of an additional child on retirement likelihood is negative. JEL Classification C36, C51, J26 Keywords grandchild, retirement, Instrumental variable, SHARE, IV, wide-ranging data, 2SLS Title The impact of grandchildren on retirement timing: evidence from SHARE data
APA, Harvard, Vancouver, ISO, and other styles

Books on the topic "Instrumental variable (IV) methods"

1

Wickens, M. R. The estimation of linear models with future rational expectations by efficient and instrumental variable methods. Southampton: Department of Economics, University of Southampton, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Bhattacharya, R. N. Proxy and instrumental variable methods in a regression model with one of the regressors missing. Leicester: University of Leicester, Department of Economics, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Instrumental variable (IV) methods"

1

Laurain, Vincent, Marion Gilson, and Hugues Garnier. "Refined Instrumental Variable Methods for Hammerstein Box-Jenkins Models." In System Identification, Environmental Modelling, and Control System Design, 27–47. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-974-1_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Gilson, Marion, Hugues Garnier, Peter C. Young, and Paul Van den Hof. "Instrumental Variable Methods for Closed-loop Continuous-time Model Identification." In Identification of Continuous-time Models from Sampled Data, 133–60. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-161-9_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Nakashima, Masaharu. "Unconditionally Stable Explicit Difference Schemes for the Variable Coefficients Parabolic Differential Equation (IV)." In Numerical Methods and Applications, 536–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36487-0_61.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Atzeni, Gianfranco, Luca G. Deidda, Marco Delogu, and Dimitri Paolini. "Drop-Out Decisions in a Cohort of Italian Universities." In Teaching, Research and Academic Careers, 71–103. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07438-7_4.

Full text
Abstract:
AbstractIn this chapter, we study the determinants of student drop-out decisions using data on a cohort of over 230,000 students enrolled in the Italian university system. The empirical analysis reveals that the probability of dropping out of university negatively correlates with high school grades and student age, controlling for the course of study and university fixed effects. The benchmark estimation suggests a negative correlation between high school final grade and drop-out probability. We also find that enrolling late at the university increases the likelihood of dropping out. In line with the literature, our results suggest that women have a lower propensity to drop out. Our dataset allows differentiating between students who leave their homes to enroll at university (off-site students) and on-site students. We find that off-site students drop out significantly less than those who study in their hometowns. We provide significant evidence that off-site students are a self-selected sample of the total population. Accordingly, we use an instrumental variable (IV) approach to identify the causal relationship. The IV estimation shows that studying off-site negatively affects drop-out decisions and more so for students growing up in the south of Italy who typically study off-site in the Center-North of Italy. Taking advantage of a more detailed dataset concerning students enrolled at the Università di Sassari, we show that the choice of the degree is also important to predict the magnitude of drop-out. Specifically, we resort to a bivariate probit specification to account for self-selection into the course of study, finding that the estimates of the determinants of drop-out and the predicted probabilities are heavily affected. Accounting for self-selection, we show that an unconditional comparison among degrees is misleading, as some degrees attract more heterogeneous students than others, as far as skills and motivation are concerned. For instance, regarding the effect of gender, we show that while the estimation without selection suggests that women drop out less, once we account for selection, the contribution of women to drop-out becomes either positive or negative, depending on which course of study they choose. In line with these results, policymakers should tailor drop-out reducing policy interventions to the specificities of each course of study.
APA, Harvard, Vancouver, ISO, and other styles
5

Manzi, Hilda, and Joseph P. Gweyi-Onyango. "Agro-ecological Lower Midland Zones IV and V in Kenya Using GIS and Remote Sensing for Climate-Smart Crop Management." In African Handbook of Climate Change Adaptation, 965–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_35.

Full text
Abstract:
AbstractFood production in Kenya and Africa in recent past has experienced vagaries of weather fluctuations which ultimately have affected crop yield. Farming in Kenya is localized in specific Agro-ecological zones, hence understanding crop growth responses in particular regions is crucial in planning and management for purposes of accelerating adoption. A number of strategies for adoption and adaptation to changing weather patterns have been deployed yet only limited challenges have been partially addressed or managed. This chapter examines previous methods used in classifying agro-ecological zones and further provides additional insightful parameters that can be adopted to enable farmers understand and adapt better to the current variable and unpredictable cropping seasons. The chapter scrutinizes past and current documented information on agro-ecological zonal valuations coupled with the use of earth observation components such as air temperature at surface, land surface temperature, evapotranspiration, soil, temperature, and soil and moisture content in order to better understand and effectively respond to new phenomena occurring as a result of climate change in the marginal agricultural areas. Significant variations in precipitation, ambient temperature, soil moisture content, and soil temperature become evident when earth observation data are used in evaluation of agro-ecological lower midland zones IV and V. The said variations cut across areas within the agro-ecological zones that have been allocated similar characteristics when assigning cropping seasons. The chapter summarizes the outcomes of various streams of contributions that have reported significant shifts or changes in rainfall and temperature patterns across Kenya and wider Eastern Africa region. The chapter highlights the need for re-evaluation of the agro-ecological zones based on the recent earth observation datasets in their diversity. The research emphasizes the use of multiple climate and soil-related parameters in understanding climate change in the other marginal areas of Kenya.
APA, Harvard, Vancouver, ISO, and other styles
6

Manzi, Hilda, and Joseph P. Gweyi-Onyango. "Agro-ecological Lower Midland Zones IV and V in Kenya Using GIS and Remote Sensing for Climate-Smart Crop Management." In African Handbook of Climate Change Adaptation, 1–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42091-8_35-1.

Full text
Abstract:
AbstractFood production in Kenya and Africa in recent past has experienced vagaries of weather fluctuations which ultimately have affected crop yield. Farming in Kenya is localized in specific Agro-ecological zones, hence understanding crop growth responses in particular regions is crucial in planning and management for purposes of accelerating adoption. A number of strategies for adoption and adaptation to changing weather patterns have been deployed yet only limited challenges have been partially addressed or managed. This chapter examines previous methods used in classifying agro-ecological zones and further provides additional insightful parameters that can be adopted to enable farmers understand and adapt better to the current variable and unpredictable cropping seasons. The chapter scrutinizes past and current documented information on agro-ecological zonal valuations coupled with the use of earth observation components such as air temperature at surface, land surface temperature, evapotranspiration, soil, temperature, and soil and moisture content in order to better understand and effectively respond to new phenomena occurring as a result of climate change in the marginal agricultural areas. Significant variations in precipitation, ambient temperature, soil moisture content, and soil temperature become evident when earth observation data are used in evaluation of agro-ecological lower midland zones IV and V. The said variations cut across areas within the agro-ecological zones that have been allocated similar characteristics when assigning cropping seasons. The chapter summarizes the outcomes of various streams of contributions that have reported significant shifts or changes in rainfall and temperature patterns across Kenya and wider Eastern Africa region. The chapter highlights the need for re-evaluation of the agro-ecological zones based on the recent earth observation datasets in their diversity. The research emphasizes the use of multiple climate and soil-related parameters in understanding climate change in the other marginal areas of Kenya.
APA, Harvard, Vancouver, ISO, and other styles
7

Bishop, Kelly C., Sehba Husain-Krautter, Jonathan D. Ketcham, Nicolai V. Kuminoff, and Corbett Schimming. "Analyzing Individual-Level Secondary Data with Instrumental Variable Methods Is Useful for Studying the Effects of Air Pollution on Dementia." In Advances in Alzheimer’s Disease. IOS Press, 2021. http://dx.doi.org/10.3233/aiad210044.

Full text
Abstract:
We hypothesize that analyzing individual-level secondary data with instrumental variable (IV) methods can advance knowledge of the long-term effects of air pollution on dementia. We discuss issues in measurement using secondary data and how IV estimation can overcome biases due to measurement error and unmeasured variables. We link air-quality data from the Environmental Protection Agency’s monitors with Medicare claims data to illustrate the use of secondary data to document associations. Additionally, we describe results from a previous study that uses an IV for pollution and finds that PM2.5’s effects on dementia are larger than non-causal associations.
APA, Harvard, Vancouver, ISO, and other styles
8

"Methods for instrumental variable analysis." In Mendelian Randomization, 59–88. Chapman and Hall/CRC, 2015. http://dx.doi.org/10.1201/b18084-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

STOICA, PETRE, BENJAMIN FRIEDLANDER, and TORSTEN SÖDERSTRÖM. "Instrumental Variable Methods for ARMA Models." In Control and Dynamic Systems, 79–150. Elsevier, 1987. http://dx.doi.org/10.1016/b978-0-12-012725-2.50006-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Chesher, Andrew, and Adam M. Rosen. "Generalized instrumental variable models, methods, and applications." In Handbook of Econometrics, 1–110. Elsevier, 2020. http://dx.doi.org/10.1016/bs.hoe.2019.11.001.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Instrumental variable (IV) methods"

1

McKelvey, Tomas. "Frequency Domain System Identification With Instrumental Variable Based Subspace Algorithm." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/vib-4252.

Full text
Abstract:
Abstract In this paper we discuss how the time domain subspace based identification algorithms can be modified in order to be applicable when the primary measurements are given as samples of the Fourier transform of the input and output signals or alternatively samples of the transfer function. An instrumental variable (IV) based subspace algorithm is presented. We show that this method is consistent if a certain rank constraint is satisfied and the frequency domain noise is zero mean with bounded covariances. An example is presented which illuminates the theoretical discussion.
APA, Harvard, Vancouver, ISO, and other styles
2

Cheng, Debo, Jiuyong Li, Lin Liu, Jiji Zhang, Thuc Duy Le, and Jixue Liu. "Ancestral Instrument Method for Causal Inference without Complete Knowledge." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/671.

Full text
Abstract:
Unobserved confounding is the main obstacle to causal effect estimation from observational data. Instrumental variables (IVs) are widely used for causal effect estimation when there exist latent confounders. With the standard IV method, when a given IV is valid, unbiased estimation can be obtained, but the validity requirement on a standard IV is strict and untestable. Conditional IVs have been proposed to relax the requirement of standard IVs by conditioning on a set of observed variables (known as a conditioning set for a conditional IV). However, the criterion for finding a conditioning set for a conditional IV needs a directed acyclic graph (DAG) representing the causal relationships of both observed and unobserved variables. This makes it challenging to discover a conditioning set directly from data. In this paper, by leveraging maximal ancestral graphs (MAGs) for causal inference with latent variables, we study the graphical properties of ancestral IVs, a type of conditional IVs using MAGs, and develop the theory to support data-driven discovery of the conditioning set for a given ancestral IV in data under the pretreatment variable assumption. Based on the theory, we develop an algorithm for unbiased causal effect estimation with a given ancestral IV and observational data. Extensive experiments on synthetic and real-world datasets demonstrate the performance of the algorithm in comparison with existing IV methods.
APA, Harvard, Vancouver, ISO, and other styles
3

Sayed, Ali H. "Time-variant structured matrices: an application to instrumental variable methods." In SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, edited by Franklin T. Luk. SPIE, 1994. http://dx.doi.org/10.1117/12.190863.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Gilson, M., H. Garnier, and P. Van den Hof. "Instrumental variable methods for continuous-time model identification in closed-loop." In Proceedings of the 2004 American Control Conference. IEEE, 2004. http://dx.doi.org/10.23919/acc.2004.1383898.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Ha, Huong, and James S. Welsh. "Model order selection for continuous time instrumental variable methods using regularization." In 2015 54th IEEE Conference on Decision and Control (CDC). IEEE, 2015. http://dx.doi.org/10.1109/cdc.2015.7402323.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Laurain, V., M. Gilson, and H. Garnier. "Refined instrumental variable methods for identifying hammerstein models operating in closed loop." In 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5400896.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Laurain, V., M. Gilson, H. Garnier, and P. C. Young. "Refined instrumental variable methods for identification of Hammerstein continuous-time Box-Jenkins models." In 2008 47th IEEE Conference on Decision and Control. IEEE, 2008. http://dx.doi.org/10.1109/cdc.2008.4738853.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Abbas, Hossam S. "Closed-Loop Identification of Input-Output LPV Models using Refined Instrumental Variable Methods." In Intelligent Systems and Control. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.744-044.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Salem, Thouraya, Manel Chetoui, and Mohamed Aoun. "Instrumental variable based methods for continuous-time linear parameter varying system identification with fractional models." In 2016 24th Mediterranean Conference on Control and Automation (MED). IEEE, 2016. http://dx.doi.org/10.1109/med.2016.7536043.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Laurain, V., M. Gilson, R. Toth, and H. Garnier. "Identification of LPV output-error and Box-Jenkins models via optimal refined instrumental variable methods." In 2010 American Control Conference (ACC 2010). IEEE, 2010. http://dx.doi.org/10.1109/acc.2010.5530665.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Instrumental variable (IV) methods"

1

Rosen, Adam, and Andrew Chesher. Generalized Instrumental Variable Models, Methods, and Applications. The IFS, August 2019. http://dx.doi.org/10.1920/wp.cem.2019.4119.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Chesher, Andrew, and Adam Rosen. Generalized instrumental variable models, methods, and applications. The IFS, July 2018. http://dx.doi.org/10.1920/wp.cem.2018.4318.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

VandenBerg, R. D., P. B. Kabanov, K E Dewing, and E. A. Atkinson. Geological and geochemical data from the Canadian Arctic Islands, part XVIII: XRF and TOC data, and formation tops in exploration wells from the Devonian clastic wedge and underlying strata, Northwest Territories and Nunavut. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329642.

Full text
Abstract:
This collection of data comprises new XRF data, TOC data, and a new table of formation tops for the lower portion of the Devonian clastic wedge (Weatherall, Cape de Bray and Blackley formations sensu Embry and Klovan, 1976) and the underlying basinal and carbonate-platform strata of variable Ordovician to Lower-Middle Devonian age. Main results include ED-XRF data for 15 well sections within the N.W.T. jurisdiction of the SW Arctic Archipelago. These XRF data were obtained in 2018- 2020 through non-destructive measurements of drillhole cutting samples using a Bruker Tracer IV instrument. Testing of these samples has been restricted to preserve them for future study as they are irreplaceable. The goal of using the non destructives XFR has given us a methodology that does not harm these samples. We find this to be a reasonable method when data is required but no destructive testing is permitted, such as in these legacy wells. Reading acquisition procedure and instrument calibrations are discussed herein. These XRF logs cover cumulatively 12,538 m of well sections, which is the best attainable physical coverage for these strata in the absence of representative cores. For each section surveyed with XRF, we provide graphical striplogs with geophysical logs, descriptive lithology, XRF elemental logs, biostratigraphic data, and, selectively, synthetic seismograms and TOC data. Scientific discussion based on these results is a subject of a separate paper-in-preparation, (Kabanov, P. 2020.)
APA, Harvard, Vancouver, ISO, and other styles
4

Yogev, David, Ricardo Rosenbusch, Sharon Levisohn, and Eitan Rapoport. Molecular Pathogenesis of Mycoplasma bovis and Mycoplasma agalactiae and its Application in Diagnosis and Control. United States Department of Agriculture, April 2000. http://dx.doi.org/10.32747/2000.7573073.bard.

Full text
Abstract:
Mycoplasma bovis and M. agalactiae are two phylogenetically related mycoplasmas which cause economically significant diseases in their respective bovine or small ruminant hosts. These organisms cause persistent asymptomatic infections that can result in severe outbreaks upon introduction of carrier animals into susceptible herds. Little is known about the mechanisms underlying mycoplasma-host interaction, variation in virulence, or of the factors enabling avoidance of the host immune system. In recent years it has become apparent that the ability of pathogenic microorganisms to rapidly alter surface antigenic structures and to fine tune their antigenicity, a phenomena called antigenic variation, is one of the most effective strategies used to escape immune destruction and to establish chronic infections. Our discovery of a novel genetic system, mediating antigenic variation in M. bovis (vsp) as well as in M. agalactiae (avg) served as a starting point for our proposal which included the following objectives: (i) Molecular and functional characterization of the variable surface lipoproteins (Vsp) system of M. bovis and comparison with the Vsp-counterpart in M. agalactiae (ii) Determination of the role of Vsp proteins in the survival of M. bovis when confronted by host defense factors, (iii) Assessment of Vsp-based genetic and antigenic typing of M. bovis and M. agalactiae for epidemiology of infection and (iv) Improvement of diagnostic tests for M. bovis and M. agalactiae based on the vsp-and vsp-analogous systems. We have carried out an extensive molecular characterization of the vsp system and unravelled the precise molecular mechanism responsible for the generation of surface antigenic variation in M. bovis. Our data clearly demonstrated that the two pathogenic mycoplasma species possess large gene families encoding variable lipoprotein antigens that apparently play an important role in immune evasion and in pathogen-host interaction during infection. Phase variable production of these antigens was found to be mediated by a novel molecular mechanism utilizing double site-specific DNA inversions via an intermediate vsp configuration. Studies in model systems indicate that phase variation of VspA is relevant in interaction between M. bovis and macrophages or monocytes, a crucial stage in pathogenesis. Using an ELISA test with captured VspA as an antigen, phase variation was shown to occur in vivo and under field conditions. Genomic rearrangements in the avg gene family of M. agalactiae were shown to occur in vivo and may well have a role in evasion of host defences and establishment of chronic infection. An epidemiological study indicated that patterns of vsp-related antigenic variation diverge rapidly in an M. bovis infected herd. Marked divergence was also found with avg-based genomic typing of M. agalactiae in chronically infected sheep. However, avg-genomic fingerprints were found to be relatively homogeneous in different animals during acute stages of an outbreak of Contagious Agalactiae, and differ between unrelated outbreaks. These data support the concept of vsp-based genomic typing but indicate the necessity for further refinement of the methodology. The molecular knowledge on these surface antigens and their encoding genes provides the basis for generating specific recombinant tools and serological methods for serodiagnosis and epidemiological purposes. Utilization of these methods in the field may allow differentiating acutely infected herds from chronic herds and disease-free herds. In addition the highly immunogenic nature of these lipoproteins may facilitate the design of protective vaccine against mycoplasma infections.
APA, Harvard, Vancouver, ISO, and other styles
5

Castellano, Mike J., Abraham G. Shaviv, Raphael Linker, and Matt Liebman. Improving nitrogen availability indicators by emphasizing correlations between gross nitrogen mineralization and the quality and quantity of labile soil organic matter fractions. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7597926.bard.

Full text
Abstract:
A major goal in Israeli and U.S. agroecosystems is to maximize nitrogen availability to crops while minimizing nitrogen losses to air and water resources. This goal has presented a significant challenge to global agronomists and scientists because crops require large inputs of nitrogen (N) fertilizer to maximize yield, but N fertilizers are easily lost to surrounding ecosystems where they contribute to water pollution and greenhouse gas concentrations. Determination of the optimum N fertilizer input is complex because the amount of N produced from soil organic matter varies with time, space and management. Indicators of soil N availability may help to guide requirements for N fertilizer inputs and are increasingly viewed as indicators of soil health To address these challenges and improve N availability indicators, project 4550 “Improving nitrogen availability indicators by emphasizing correlations between gross nitrogen mineralization and the quality and quantity of labile organic matter fractions” addressed the following objectives: Link the quantity and quality of labile soil organic matter fractions to indicators of soil fertility and environmental quality including: i) laboratory potential net N mineralization ii) in situ gross N mineralization iii) in situ N accumulation on ion exchange resins iv) crop uptake of N from mineralized soil organic matter sources (non-fertilizer N), and v) soil nitrate pool size. Evaluate and compare the potential for hot water extractable organic matter (HWEOM) and particulate organic matter quantity and quality to characterize soil N dynamics in biophysically variable Israeli and U.S. agroecosystems that are managed with different N fertility sources. Ultimately, we sought to determine if nitrogen availability indicators are the same for i) gross vs. potential net N mineralization processes, ii) diverse agroecosystems (Israel vs. US) and, iii) management strategies (organic vs. inorganic N fertility sources). Nitrogen availability indicators significantly differed for gross vs. potential N mineralization processes. These results highlight that different mechanisms control each process. Although most research on N availability indicators focuses on potential net N mineralization, new research highlights that gross N mineralization may better reflect plant N availability. Results from this project identify the use of ion exchange resin (IERs) beads as a potential technical advance to improve N mineralization assays and predictors of N availability. The IERs mimic the rhizosphere by protecting mineralized N from loss and immobilization. As a result, the IERs may save time and money by providing a measurement of N mineralization that is more similar to the costly and time consuming measurement of gross N mineralization. In further search of more accurate and cost-effective predictors of N dynamics, Excitation- Emission Matrix (EEM) spectroscopy analysis of HWEOM solution has the potential to provide reliable indicators for changes in HWEOM over time. These results demonstrated that conventional methods of labile soil organic matter quantity (HWEOM) coupled with new analyses (EEM) may be used to obtain more detailed information about N dynamics. Across Israeli and US soils with organic and inorganic based N fertility sources, multiple linear regression models were developed to predict gross and potential N mineralization. The use of N availability indicators is increasing as they are incorporated into soil health assessments and agroecosystem models that guide N inputs. Results from this project suggest that some soil variables can universally predict these important ecosystem process across diverse soils, climate and agronomic management. BARD Report - Project4550 Page 2 of 249
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Instrumental variable (IV) methods' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography