Estimating the effect of the 2008 financial crisis on GNI in Greece and Iceland: A synthetic control approach

The purpose of this thesis is to conduct a comparative study in order to estimate the impact of the financial crisis to the GNI of Greece and Iceland. By applying synthetic control matching (a relatively new methodology) the study intends to compare the two countries, thus deducting conclusions about good or bad measures adopted. The results indicate that in both cases the adopted measures were not the optimal ones, since the synthetic counterfactual appear to perform better than the actual Greece and Iceland. Moreover, it is shown that Iceland reacted better to the shock it was exposed. However, different characteristics of the two countries impede the application of Icelandic actions in the Greek case.

The Synthetic Control Chart Based on Two Sample Variances for Monitoring the Covariance Matrix

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Synthetic control chart for monitoring the pprocess mean and variance

In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.

Monitoring the process mean and variance using a synthetic control chart with two-stage testing

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A synthetic control chart for monitoring the process mean and variance

Purpose - The aim of this paper is to present a synthetic chart based on the non-central chi-square statistic that is operationally simpler and more effective than the joint X̄ and R chart in detecting assignable cause(s). This chart will assist in identifying which (mean or variance) changed due to the occurrence of the assignable causes. Design/methodology/approach - The approach used is based on the non-central chi-square statistic and the steady-state average run length (ARL) of the developed chart is evaluated using a Markov chain model. Findings - The proposed chart always detects process disturbances faster than the joint X̄ and R charts. The developed chart can monitor the process instead of looking at two charts separately. Originality/value - The most important advantage of using the proposed chart is that practitioners can monitor the process by looking at only one chart instead of looking at two charts separately. © Emerald Group Publishing Limted.

Synthetic control charts with two-stage sampling for monitoring bivariate processes

In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control bivariate processes. During the first stage, one item of the sample is inspected and two correlated quality characteristics (x;y) are measured. If the Hotelling statistic T1 2 for these individual observations of (x;y) is lower than a specified value UCL 1 the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the Hotelling statistic T2 2 for the sample means of (x;y) is computed. When the statistic T2 2 is larger than a specified value UCL2, the sample is classified as nonconforming. According to the synthetic control chart procedure, the signal is based on the number of conforming samples between two neighbor nonconforming samples. The proposed chart detects process disturbances faster than the bivariate charts with variable sample size and it is from the practical viewpoint more convenient to administer.

Revisiting the synthetic control estimator

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. The SC relies on the assumption that there is a weighted average of the control units that reconstruct the potential outcome of the treated unit in the absence of treatment. If these weights were known, then one could estimate the counterfactual for the treated unit using this weighted average. With these weights, the SC would provide an unbiased estimator for the treatment effect even if selection into treatment is correlated with the unobserved heterogeneity. In this paper, we revisit the SC method in a linear factor model where the SC weights are considered nuisance parameters that are estimated to construct the SC estimator. We show that, when the number of control units is fixed, the estimated SC weights will generally not converge to the weights that reconstruct the factor loadings of the treated unit, even when the number of pre-intervention periods goes to infinity. As a consequence, the SC estimator will be asymptotically biased if treatment assignment is correlated with the unobserved heterogeneity. The asymptotic bias only vanishes when the variance of the idiosyncratic error goes to zero. We suggest a slight modification in the SC method that guarantees that the SC estimator is asymptotically unbiased and has a lower asymptotic variance than the difference-in-differences (DID) estimator when the DID identification assumption is satisfied. If the DID assumption is not satisfied, then both estimators would be asymptotically biased, and it would not be possible to rank them in terms of their asymptotic bias.

The Power of the Synthetic Control Method

The synthetic control method (SCM) is a new, popular method developed for the purpose of estimating the effect of an intervention when only one single unit has been exposed. Other similar, unexposed units are combined into a synthetic control unit intended to mimic the evolution in the exposed unit, had it not been subject to exposure. As the inference relies on only a single observational unit, the statistical inferential issue is a challenge. In this paper, we examine the statistical properties of the estimator, study a number of features potentially yielding uncertainty in the estimator, discuss the rationale for statistical inference in relation to SCM, and provide a Web-app for researchers to aid in their decision of whether SCM is powerful for a specific case study. We conclude that SCM is powerful with a limited number of controls in the donor pool and a fairly short pre-intervention time period. This holds as long as the parameter of interest is a parametric specification of the intervention effect, and the duration of post-intervention period is reasonably long, and the fit of the synthetic control unit to the exposed unit in the pre-intervention period is good.

Size Control and Magnetic Property Trends in Cobalt Ferrite Nanoparticles Synthesized Using an Aqueous Chemical Route

Cobalt ferrite (CoFe2O4) is an engineering material which is used for applications such as magnetic cores, magnetic switches, hyperthermia based tumor treatment, and as contrast agents for magnetic resonance imaging. Utility of ferrites nanoparticles hinges on its size, dispersibility in solutions, and synthetic control over its coercivity. In this work, we establish correlations between room temperature co-precipitation conditions, and these crucial materials parameters. Furthermore, post-synthesis annealing conditions are correlated with morphology, changes in crystal structure and magnetic properties. We disclose the synthesis and process conditions helpful in obtaining easily sinterable CoFe2O4 nanoparticles with coercive magnetic flux density (H-c) in the range 5.5-31.9 kA/m and M-s in the range 47.9-84.9 A.m(2)Kg(-1). At a grain size of similar to 54 +/- 2 nm (corresponding to 1073 K sintering temperature), multi-domain behavior sets in, which is indicated by a decrease in H-c. In addition, we observe an increase in lattice constant with respect to grain size, which is the inverse of what is expected of in ferrites. Our results suggest that oxygen deficiency plays a crucial role in explaining this inverse trend. We expect the method disclosed here to be a viable and scalable alternative to thermal decomposition based CoFe2O4 synthesis. The magnetic trends reported will aid in the optimization of functional CoFe2O4 nanoparticles

Cherry picking with synthetic controls

The synthetic control (SC) method has been recently proposed as an alternative method to estimate treatment e ects in comparative case studies. Abadie et al. [2010] and Abadie et al. [2015] argue that one of the advantages of the SC method is that it imposes a data-driven process to select the comparison units, providing more transparency and less discretionary power to the researcher. However, an important limitation of the SC method is that it does not provide clear guidance on the choice of predictor variables used to estimate the SC weights. We show that such lack of speci c guidances provides signi cant opportunities for the researcher to search for speci cations with statistically signi cant results, undermining one of the main advantages of the method. Considering six alternative speci cations commonly used in SC applications, we calculate in Monte Carlo simulations the probability of nding a statistically signi cant result at 5% in at least one speci cation. We nd that this probability can be as high as 13% (23% for a 10% signi cance test) when there are 12 pre-intervention periods and decay slowly with the number of pre-intervention periods. With 230 pre-intervention periods, this probability is still around 10% (18% for a 10% signi cance test). We show that the speci cation that uses the average pre-treatment outcome values to estimate the weights performed particularly bad in our simulations. However, the speci cation-searching problem remains relevant even when we do not consider this speci cation. We also show that this speci cation-searching problem is relevant in simulations with real datasets looking at placebo interventions in the Current Population Survey (CPS). In order to mitigate this problem, we propose a criterion to select among SC di erent speci cations based on the prediction error of each speci cations in placebo estimations

Synthetic Approaches to Flexible Fluorescent Conjugated Polymers

Conjugated polymers (CPs) are intrinsically fluorescent materials that have been used for various biological applications including imaging, sensing, and delivery of biologically active substances. The synthetic control over flexibility and biodegradability of these materials aids the understanding of the structure-function relationships among the photophysical properties, the self-assembly behaviors of the corresponding conjugated polymer nanoparticles (CPNs), and the cellular behaviors of CPNs, such as toxicity, cellular uptake mechanisms, and sub-cellular localization patterns. Synthetic approaches towards two classes of flexible CPs with well-preserved fluorescent properties are described. The synthesis of flexible poly(p-phenylenebutadiynylene)s (PPBs) uses competing Sonogashira and Glaser coupling reactions and the differences in monomer reactivity to incorporate a small amount (~10%) of flexible, non-conjugated linkers into the backbone. The reaction conditions provide limited control over the proportion of flexible monomer incorporation. Improved synthetic control was achieved in a series of flexible poly(p-phenyleneethynylene)s (PPEs) using modified Sonogashira conditions. In addition to controlling the degree of flexibility, the linker provides disruption of backbone conjugation that offers control of the length of conjugated segments within the polymer chain. Therefore, such control also results in the modulation of the photophysical properties of the materials. CPNs fabricated from flexible PPBs are non-toxic to cells, and exhibit subcellular localization patterns clearly different from those observed with non-flexible PPE CPNs. The subcellular localization patterns of the flexible PPEs have not yet been determined, due to the toxicity of the materials, most likely related to the side-chain structure used in this series. The study of the effect of CP flexibility on self-assembly reorganization upon polyanion complexation is presented. Owing to its high rigidity and hydrophobicity, the PPB backbone undergoes reorganization more readily than PPE. The effects are enhanced in the presence of the flexible linker, which enables more efficient π-π stacking of the aromatic backbone segments. Flexibility has minimal effects on the self-assembly of PPEs. Understanding the role of flexibility on the biophysical behaviors of CPNs is key to the successful development of novel efficient fluorescent therapeutic delivery vehicles.

Synthetic approaches to flexible fluorescent conjugated polymers

Conjugated polymers (CPs) are intrinsically fluorescent materials that have been used for various biological applications including imaging, sensing, and delivery of biologically active substances. The synthetic control over flexibility and biodegradability of these materials aids the understanding of the structure-function relationships among the photophysical properties, the self-assembly behaviors of the corresponding conjugated polymer nanoparticles (CPNs), and the cellular behaviors of CPNs, such as toxicity, cellular uptake mechanisms, and sub-cellular localization patterns. ^ Synthetic approaches towards two classes of flexible CPs with well-preserved fluorescent properties are described. The synthesis of flexible poly( p-phenylenebutadiynylene)s (PPBs) uses competing Sonogashira and Glaser coupling reactions and the differences in monomer reactivity to incorporate a small amount (∼10%) of flexible, non-conjugated linkers into the backbone. The reaction conditions provide limited control over the proportion of flexible monomer incorporation. Improved synthetic control was achieved in a series of flexible poly(p-phenyleneethynylene)s (PPEs) using modified Sonogashira conditions. In addition to controlling the degree of flexibility, the linker provides disruption of backbone conjugation that offers control of the length of conjugated segments within the polymer chain. Therefore, such control also results in the modulation of the photophysical properties of the materials. ^ CPNs fabricated from flexible PPBs are non-toxic to cells, and exhibit subcellular localization patterns clearly different from those observed with non-flexible PPE CPNs. The subcellular localization patterns of the flexible PPEs have not yet been determined, due to the toxicity of the materials, most likely related to the side-chain structure used in this series. ^ The study of the effect of CP flexibility on self-assembly reorganization upon polyanion complexation is presented. Owing to its high rigidity and hydrophobicity, the PPB backbone undergoes reorganization more readily than PPE. The effects are enhanced in the presence of the flexible linker, which enables more efficient π-π stacking of the aromatic backbone segments. Flexibility has minimal effects on the self-assembly of PPEs. Understanding the role of flexibility on the biophysical behaviors of CPNs is key to the successful development of novel efficient fluorescent therapeutic delivery vehicles.^

Synthetic portfolio for event studies: Estimating the effects of volatility call auctions

We propose a method denoted as synthetic portfolio for event studies in market microstructure that is particularly interesting to use with high frequency data and thinly traded markets. The method is based on Synthetic Control Method and provides a robust data driven method to build a counterfactual for evaluating the effects of the volatility call auctions. We find that SMC could be used if the loss function is defined as the difference between the returns of the asset and the returns of a synthetic portfolio. We apply SCM to test the performance of the volatility call auction as a circuit breaker in the context of an event study. We find that for Colombian Stock Market securities, the asynchronicity of intraday data reduces the analysis to a selected group of stocks, however it is possible to build a tracking portfolio. The realized volatility increases after the auction, indicating that the mechanism is not enhancing the price discovery process.