Resurgence of the Endogeneity-Backed Instrumental Variable Methods

This paper investigates the nature of the IV method for tackling endogeneity. By tracing the rise and fall of the method in macroeconometrics and its subsequent revival in microeconometrics, it pins the method down to an implicit model respecification device—breaking the circular causality of simultaneous relations by redefining it as an asymmetric one conditioning on a non-optimal conditional expectation of the assumed endogenous explanatory variable, thus rejecting that variable as a valid conditional variable. The revealed nature explains why the IV route is popular for models where endogeneity is superfluous whereas measurement errors are of the key concern

Time to Demystify Endogeneity Bias

This study exposes the flaw in defining endogeneity bias by correlation between an explanatory variable and the error term of a regression model. Through dissecting the links which have led to entanglement of measurement errors, simultaneity bias, omitted variable bias and self-selection bias, the flaw is revealed to stem from a Utopian mismatch of reality directly with single explanatory variable models. The consequent estimation-centered route to circumvent the correlation is shown to be committing a type III error. Use of single variable based ‘consistent’ estimators without consistency of model with data can result in significant distortion of causal postulates of substantive interest. This strategic error is traced to a loss in translation of those causal postulates into multivariate conditional models appropriately designed through efficient combination of substantive knowledge with data information. Endogeneity bias phobia will be uprooted once applied modelling research is centered on such designs

Criticizing the Lucas Critique: Macroeconometricians’ Response to Robert Lucas

The standard history of macroeconomics considers Lucas (1976)– “the Lucas Critique”–as a path-breaking innovation for the discipline. According to this view Lucas’s article dismissed the traditional macroeconometric practice calling for new ways of conceiving the quantitative evaluation of economic policies. The Lucas Critique is considered, nowadays, as a fundamental principle of macroeconomic modeling (Woodford, 2003). The interpretation and the application of the Critique, however, represent still unsolved issues in economics (Chari et al., 2008). Even if the influence of Lucas’s contribution cannot be neglected, something seems to be missing in the narrative: the reactions of the economists that were directly targeted by the Critique. Modeling practices of economic policy evaluation were not overthrown immediately after Lucas (1976), creating a divide between theoretical and applied macroeconomics (Brayton et al., 1997). In the first section we propose a careful account of Lucas’s argument and of some of the previous works anticipating the substantial outline of the Critique (like Frisch’s notion of autonomy). Second, we bring our own interpretation of Lucas (1976). We find two points of view in Lucas's paper: a prescriptive one that tell how to build a good macroeconometric model (it is the standard interpretation of the article); a positive one that relies on the fact that the Lucas critique could be seen as an attempt to explain a real-world phenomenon: stagflation. Third, we classify the reactions of the Keynesian macroeconometricians following this line of interpretation. On the prescriptive side, the Keynesians protested against the New Classical solution to the Lucas critique (the use of the rational expectation hypothesis among other things). Klein, for instance, proposed an alternative microfoundational program to empirically study the formation of expectations. On the positive side, the Keynesians put into question the relevance of the Lucas Critique to explain the rise of both unemployment and inflation in the 1970s. They tried to test the impact of policy regime changes and of shifts in agents' behavior. We argue that the explanation of the stagflation was elsewhere. The purpose of this paper is to study the reactions of the macroeconometricians criticized by Lucas. We focus especially on those macroeconometricians who worked on policy evaluation and who held an expertise position in governmental institutions. We categorize the different reactions to the Critique, in order to enrich the understanding of the evolution of modeling and expertise practices through the analysis of the debates–which have not yet been completely solved

How Credible Are Shrinking Wage Elasticities of Married Women Labour Supply?

This paper delves into the well-known phenomenon of shrinking wage elasticities for married women in the US over recent decades. The results of a novel model experimental approach via sample data ordering unveil considerable heterogeneity across different wage groups. Yet, surprisingly constant wage elasticity estimates are maintained within certain wage groups over time. In addition to those constant wage elasticity estimates, we find that the composition of working women into different wage groups has changed considerably, resulting in shrinking wage elasticity estimates at the aggregate level. These findings would be impossible to obtain had we not dismantled and discarded the instrumental variable estimation route

Let's take the bias out of econometrics

This study exposes the cognitive flaws of ‘endogeneity bias’. It examines how conceptualisation of the bias has evolved to embrace all major econometric problems, despite extensive lack of hard evidence. It reveals the crux of the bias – a priori rejection of causal variables as conditionally valid ones, and of the bias correction by consistent estimators – modification of those variables by non-uniquely and non-causally generated regressors. It traces the flaws to misconceptions about error terms and estimation consistency. It highlights the need to shake off the bias to let statistical learning play an active and formal role in econometrics. JEL classification: B23, B40, C10, C5

Time to Demystify Endogeneity Bias

This study exposes the flaw in defining endogeneity bias by correlation between an explanatory variable and the error term of a regression model. Through dissecting the links which have led to entanglement of measurement errors, simultaneity bias, omitted variable bias and self-selection bias, the flaw is revealed to stem from a Utopian mismatch of reality directly with single explanatory variable models. The consequent estimation-centered route to circumvent the correlation is shown to be committing a type III error. Use of single variable based ‘consistent’ estimators without consistency of model with data can result in significant distortion of causal postulates of substantive interest. This strategic error is traced to a loss in translation of those causal postulates into multivariate conditional models appropriately designed through efficient combination of substantive knowledge with data information. Endogeneity bias phobia will be uprooted once applied modelling research is centered on such designs

Characterizing a Novel Metabolic Pathogenic Mechanism in Familial Hemiplegic Migraine

Migraine, an episodic neurological disorder, afflicts about 1 in 10 people at least monthly, yet the underlying pathophysiological mechanisms remain poorly understood. The prototypical monogenic migraine disorder, Familial Hemiplegic Migraine, theoretically presents an excellent opportunity for preclinical modeling, but thus far animal models of migraine have failed to recapitulate the severe migraine aura symptoms of episodic paralysis and ataxia. Mutations that cause Familial Hemiplegic Migraine occur in one of three genes, two neuronal ion channels, and interestingly, the astrocytic α2-Na/K ATPase. In the case of α2-Na/K ATPase, mutations primarily result in loss of protein function. As migraine is thought to be a disease of primarily neuronal hyperexcitability, it is unclear how a loss of α2-Na/K ATPase in astrocytes can confer hyperexcitability non-cell autonomously. To better characterize the sequelae stemming from loss of α2-Na/K ATPase in the brain, we generated α2-Na/K ATPase conditional knockout mice using an astrocyte-selective Cre driver. To our surprise, conditional knockout mice developed episodic paralysis and ataxia not unlike that seen in Familial Hemiplegic Migraine patients. Familial Hemiplegic Migraine motor symptoms present as part of the migraine aura, a set of neurological symptoms associated with a slow wave of synchronized neuronal activity followed by silence known as cortical spreading depression. Using widefield imaging of hemodynamics and neuronal activity via intrinsic optical signal and genetically encoded calcium indicators respectively, we discovered that unanaesthetized conditional knockout mice exhibit cortical spreading depression spontaneously at a similar frequency as paralysis bouts. Moreover, EEG abnormalities known as low voltage activity reliably accompanied cortical spreading depression. By recording continuous bilateral EEG activity in awake and behaving mice, we showed that low voltage activity is coincident with episodes of paralysis and ataxia. In sum, this data suggests that α2-Na/K ATPase conditional knockout mice model Familial Hemiplegic Migraine in an entirely novel way because they develop spontaneous migraine aura and associated motor symptoms. Next, we probed the pathogenic mechanisms of migraine in the conditional knockout mice by performing bulk and astrocyte-enriched RNA-Sequencing on cortex from mice prior to the onset of paralysis symptoms. From these studies, we discovered dysregulated metabolic pathways in the astrocytes, particularly in pathways related to amino acid metabolism. We next performed metabolomics and intersected the bioinformatics data with the metabolite levels. The metabolism network analysis revealed that serine, an uncharged, polar amino acid, is highly upregulated, as are the enzymes and other metabolites closely related to it in the network. Furthermore, HPLC verified that the levels of both enantiomers of serine, D- and L-, are significantly increased. D-serine is a particularly relevant amino acid to neurons because it serves as a co-agonist to the NMDA glutamate receptor, meaning that excess D-serine could theoretically confer neuronal hyperexcitability. We tested the hypothesis that excess serine contributes to the development of migraine aura motor symptoms in conditional knockout mice by implementing a diet with no serine or metabolically related amino acid glycine. Mass spectrometry verified that the serine/glycine free diet substantially lowered the levels of serine in the brain. Strikingly, conditional knockout mice on the serine/glycine free diet take nearly twice as long to develop paralysis symptoms, and symptoms are significantly less severe. Moreover, their motor function is significantly better for the duration of their lives that conditional knockout mice on the control diet. In sum, these studies suggest a novel metabolic pathogenic mechanism in Familial Hemiplegic Migraine. We anticipate that future studies will clarify mechanistic details driving serine buildup after astrocytic α2-Na/K ATPase loss and investigate the therapeutic potential of serine-lowering diets