scholarly journals A Generalized Non-Parametric Instrumental Variable-Control Function Approach to Estimation in Nonlinear Settings

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Kyoo il Kim ◽  
Amil Petrin
Keyword(s):  
Instrumental Variables ◽  
Conditional Expectation ◽  
Control Function ◽  
Structural Function ◽  
Conditional Moment ◽  
Conditional Mean ◽  
Endogenous Variables ◽  
Standard Linear ◽  
And Control ◽  
Non Parametric

Abstract When the endogenous variables enter non-parametrically into the regression equation standard linear instrumental variables approaches fail. Two existing solutions are the non-parametric instrumental variables (NPIVs) estimators, which are based on a set of conditional moment restrictions (CMRs), and the control function (CF) estimators, which use conditional mean independence (CMI) restrictions. Our first contribution is to show that – similar to CMI – the CMR place shape restrictions on the conditional expectation of the error given the instruments and endogenous variables that are sufficient for identification, and we call our new estimator based on these restrictions the CMR-CF estimator. Our second contribution is to develop an estimator for non-linear and non-parametric settings that can combine both CMR and CMI restrictions, which cannot be done in either the NPIV nor the non-parametric CF setting. This new “Generalized CMR-CF” uses both CMR and CMI restrictions together by allowing the conditional expectation of the structural error to depend on both instruments and control variables. When sieves are used to approximate both the structural function and the CF our estimator reduces to a series of least squares regressions. Our Monte Carlos illustrate that our new estimator performs well across several economic settings.

scholarly journals Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments

2015 ◽  
Vol 105 (5) ◽  
pp. 486-490 ◽  
Author(s):  
Victor Chernozhukov ◽  
Christian Hansen ◽  
Martin Spindler
Keyword(s):  
Sample Size ◽  
Instrumental Variables ◽  
Linear Models ◽  
Demand Estimation ◽  
Control Variables ◽  
Valid Inference ◽  
Endogenous Variables ◽  
And Control ◽  
Exogenous Control

We consider estimation of and inference about coefficients on endogenous variables in a linear instrumental variables model where the number of instruments and exogenous control variables are each allowed to be larger than the sample size. We work within an approximately sparse framework that maintains that the signal available in the instruments and control variables may be effectively captured by a small number of the available variables. We provide a LASSO-based method for this setting which provides uniformly valid inference about the coefficients on endogenous variables. We illustrate the method through an application to demand estimation.

A POWER CONSUMPTION ACTIVITY BASED HETEROGENEOUS SOA FRAMEWORK FOR CONTEXT-AWARE HOME SERVICES

2011 ◽  
Vol 20 (07) ◽  
pp. 1211-1230 ◽  
Author(s):  
HYUN SANG CHO ◽  
TAKEKAZU KATO ◽  
TATSUYA YAMAZAKI ◽  
MINSOO HAHN
Keyword(s):  
Web Services ◽  
Power Consumption ◽  
Service Oriented Architecture ◽  
Control Function ◽  
Home Network ◽  
Network System ◽  
Context Aware ◽  
Flexible Architecture ◽  
And Control ◽  
Monitor And Control

The home network is one of the emerging areas from the last century. However, the growth of the home network market is stationary at present. This paper describes the limitations of the home network system and the requirements for overcoming the current limitations. Also described is a new home network service system known as COWS and its easy installation and scalable operation. COWS consists of power consumption monitor and control devices along with a service server that is a complementary combination of Open Service Gateway initiative (OSGi) and web services. A home network system has a dynamic, heterogeneous, distributed, and scalable topology. Service Oriented Architecture (SOA) has been proposed as a solution that satisfies the requirement of a home network, and OSGi and web services are two successful SOA-based frameworks. An included service server has a flexible architecture that consists of a core and extendable service packages. A power consumption monitor and control function provides useful context information for activity-based context-aware services and optimizes the power consumption. The system can be installed easily into existing and new houses to solve the current barrier of the popularization of home network services.

ROUTING IMPLEMENTATION BASED-ON SOFTWARE DEFINED NETWORK USING RYU CONTROLLER AND OPENVSWITCH

2016 ◽  
Vol 78 (5) ◽  
Author(s):  
Yuli Sun Hariyani ◽  
Indrarini Dyah Irawati ◽  
Danu Dwi S. ◽  
Mohammad Nuruzzamanirridha
Keyword(s):  
Control Function ◽  
Raspberry Pi ◽  
Small Scale ◽  
Software Defined Network ◽  
Standard Protocol ◽  
Open Flow ◽  
Control Functions ◽  
Forward Function ◽  
And Control ◽  
Sdn Controller

Open Flow is a standard protocol for differentiating forward function and control functions to facilitate the management of big network of SDN. The research have been carried out before using the emulator SDN Mininet. However Mininet has many shortcomings, such as the performance of which is less than the maximum due to simulation. Then some researchers also use the Net-FPGA as device. This device is less suitable for small scale because the prices are quite expensive and programming is quite complicated. In this study, SDN implementation carried out using OpenvSwitch as forwarding function mounted on TP-Link that has modificated using openwrt as firmware and Raspberry Pi with Ryu SDN Controller as control functions. The result shows that routing static can be implemented on SDN Network which use Raspberry Pi with Ryu Controller as control function with average bandwith 536.0909 Mbits/sec and average uptime network is 10.45 second.

scholarly journals Autonomic Nervous System Is Related to Inhibitory and Control Function Through Functional Inter-Region Connectivities of OFC in Major Depression

2020 ◽  
Vol Volume 16 ◽  
pp. 235-247 ◽  
Author(s):  
Hongaling Zhou ◽  
Lingling Hua ◽  
Haiteng Jiang ◽  
Zongpeng Dai ◽  
yinglin han ◽  
...  
Keyword(s):  
Nervous System ◽  
Autonomic Nervous System ◽  
Major Depression ◽  
Control Function ◽  
Autonomic Nervous ◽  
And Control

Implementing Valid Two-Step Identification-Robust Confidence Sets for Linear Instrumental-Variables Models

2018 ◽  
Vol 18 (4) ◽  
pp. 803-825 ◽  
Author(s):  
Liyang Sun
Keyword(s):  
Monte Carlo ◽  
Instrumental Variables ◽  
Projection Method ◽  
Econometric Models ◽  
Confidence Sets ◽  
Weak Instruments ◽  
Wald Tests ◽  
Endogenous Variables ◽  
Married Female ◽  
F Statistics

In this article, we consider inference in the linear instrumental-variables models with one or more endogenous variables and potentially weak instruments. I developed a command, twostepweakiv, to implement the two-step identification-robust confidence sets proposed by Andrews (2018, Review of Economics and Statistics 100: 337–348) based on Wald tests and linear combination tests (Andrews, 2016, Econometrica 84: 2155–2182). Unlike popular procedures based on first-stage F statistics (Stock and Yogo, 2005, Testing for weak instruments in linear IV regression, in Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg), the two-step identification-robust confidence sets control coverage distortion without assuming the data are homoskedastic. I demonstrate the use of twostepweakiv with an example of analyzing the effect of wages on married female labor supply. For inference on subsets of parameters, twostepweakiv also implements the refined projection method (Chaudhuri and Zivot, 2011, Journal of Econometrics 164: 239–251). I illustrate that this method is more powerful than the conventional projection method using Monte Carlo simulations.

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