R ivreg with fixed effects
R ivreg with fixed effects. fml = z~x+y | fe_1+fe_2. I also need to weight by county population. For example If I am concerned about possible endogeneity with the variable "Income" so I use "Balance" as an IV does the Wu-Hausman test being statically significant such as that in the model iv. External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. Previous message: [R] ivreg with fixed effect in R? Next message: [R] ivreg with fixed effect in R? Messages sorted by: More information about the R-help mailing list Sergio Correia, 2018. Upper and lower endpoints of the confidence interval for the effect of interest beta, for each of the methods in method. I have 2 related questions. Apr 24, 2022 · ci. 4 of the book) such that the IV estimate of the long-run elasticity of demand for cigarettes we consider the most trustworthy is −0. I have 3 variables in my function, D (indicator variable), tau (indicator variable), and rc (continuous variable). It can estimate not only OLS regressions but two-stage least squares, instrumental-variable regressions, and linear GMM (via the ivreg2 and ivregress commands). ) is derived from and supersedes the You signed in with another tab or window. "IVREGHDFE: Stata module for extended instrumental variable regressions with multiple levels of fixed effects," Statistical Software Components S458530, Boston College Department of Economics. Procedures are included for use with GLM, ivreg, plm Description. Oct 4, 2021 · The feols() function from the fixest package was designed for OLS models that have lots of fixed effects (i. st: ivreg with fixed effects. 8), andWooldridge Description. Regression with Time Fixed Effects. xtreg estimates within-group variation by computing the differences between observed values and their means. Note that exogenous regressors have to be included as instruments for themselves. An implementation of instrumental variables regression using two-stage least-squares (2SLS) estimation, based on the ivreg() function previously in the AER package. reg support that the variable "Income" is If the two variables were used as fixed-effects in the estimation, you can leave it blank with vcov = "twoway" (assuming var1 [resp. I am using ivreg and ivmodel in R to apply a 2SLS. e. However, I am having issues with the syntax specifying an estimation without further exogenous controls. Below is how I've always found it easiest to extract the individuals' fixed effects and random effects components in the lme4 -package. So far, I have gathered an unbalanced panel data set that contains student attainment data from IPEDS and Labor Force stats from American Fact Finder. where x1 and x1 are the endogenous variables I would like to instrument, w is an exogenous variable, and e is the residual. First question: When using fixed effects, variables that are invariant over time will get washed out by the firm/subject level fixed effect. For balanced data, you should get identical estimates. I have two instruments for Var1. Jan 25, 2015 · I'm trying to wrap my head around interpreting the diagnostics of the ivreg() command in R, from the {AER} package. Additional features include: Instrumental variables is a popular method in epidemiology and related fields, to estimate causal effects in the presence of unmeasured confounding. The following option is available with xtivreg but is not shown in the dialog box: coeflegend; see[R] estimation options. Recently, the methodology has been extended in several directions Next message (by thread): [R] print data. Jan 23, 2020 · The normal practice is to calculate the interactions first and then for any interactions that include the endogenous variables, include them in the list of endogenous variables for ivreg or ivreg2. District implied district fixed effect. [email protected] Subject. I intend to run instrumental variable regressions with fixed effects using the fixest package's feols function. y = ax1x2 + bx1x3 + cx4 + e y = a x 1 x 2 + b x 1 x 3 + c Jan 1, 2008 · We provide a set of conditions sufficient for consistency of a general class of fixed effects instrumental variables (FE-IV) estimators in the context of a correlated random coefficient panel data model, where one ignores the presence of individual-specific slopes. a (x2 = x3), fe Use between-effects estimator and includeindicatorsfor levels of b as instruments May 28, 2022 · In a recent study using one period cross-section data which applied IV estimation approach, stated that: " District Fixed Effect " is applied and robust "Standard Error" is clustered at "District " level. 2). , Current serial correlation tests for panel models are cumbersome to use, not suited for fixed-effects models, or limited to first-order autocorrelation. A formula representing the relation to be estimated. This difference is due to a slight variation in the implementation: see plm 's vignette , section "Unbalanced Panels" and especially the paper by Cottrell (2017 . We’re going to use the wbstats package to download country-level data from the World Bank for May 9, 2023 · For the fixed-effects model, . The main ivreg() model-fitting function is designed to provide a workflow as similar as possible to standard lm() regression. Please refer to the introduction for a walk-through. xtreg n w k if year>=1978 & year<=1982, fe . Zeileis at uibk. Fixed Effects. I can't figure out on how to insert model diagnostics as provided by the summary of ivreg(). Next, IV regression is used for estimating the elasticity of the demand for cigarettes — a classical example where May 31, 2021 · The ivreg package (by John Fox , Christian Kleiber, and Achim Zeileis) provides a comprehensive implementation of instrumental variables regression using two-stage least-squares (2SLS) estimation. The regression is specified in this manner because the ratio between a a and b b is of importance. Thu, 1 Sep 2005 05:57:10 -0700 (PDT) Dear all, I am estimating a production function with fixed effects and clustered standard errors, using ivreg. For a general discussion of instrumental variables, seeBaum(2006), Cameron and Trivedi (2005; 2010, chap. Namely weak instruments tests, Wu-Hausmann and 9. It can also handle instrumental variables (which we’ll get to later in the semester). Then one interpretation of your model is that you have estimated country effects at 2005 and country effects at 2010, with the difference = the interaction estimate. My two instruments are z1 and z2. The fixed effects model can be generalized to contain more than just one determinant of \(Y\) that is correlated with \(X\) and changes over time. This is, at least, what in principle is done by ivreg2, when using many fixed effects. I just added a year dummy for year fixed effects. I'm trying to run a 2SLS model in R and I'm having a rough time. Thus I ran a 2-stage model. It actually extracts the corresponding fit to each observation. I have a couple of problems however that I can't seem to solve myself. 4 Regression with Time Fixed Effects; 10. There is some question about this: Maurice J. Apr 27, 2015 · To correct that, either you can run your model using the cross-sectional areg or regress commands in Stata which can be done by creating fixed effect dummies of your panel variable. here i. region _Iregion_1-4 (naturally coded; _Iregion_1 omitted) 5. We would like to show you a description here but the site won’t allow us. Supports fixed slopes (different slopes per individual). It’s a fantastic way to run models in R. 0e-09) note: variable #6 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol May 29, 2024 · If the two variables were used as fixed-effects in the estimation, you can leave it blank with vcov = "twoway" (assuming var1 [resp. Description. ## R code. The site also provides the modified summary function for both one- and two-way clustering. The data looks as follows: An object of class "iv_robust". est store fe Effect and effect construct an "eff" object for a term (usually a high-order term) in a regression that models a response as a linear function of main effects and interactions of factors and covariates. 2nd] fixed-effect). This file demonstrates three approaches to estimating “fixed effects” models (remember this is what economists call “fixed effects”, but other disciplines use “fixed effects” to refer to something different). Jul 18, 2019 · s1. lm. Such factors are not directly observable or measurable but one needs to find a way to estimate their effects Jun 14, 2020 · Hello Everyone! I am new to STATA and I am having trouble reporting the Adjusted R2 When I run a regression with fixed effects and clustered standard errors, only the R2 is reported 10. Would that remove the issue? Data. fixest: Fast and user-friendly fixed-effects estimation. 5 The Fixed Effects Regression Assumptions and Standard Errors for Fixed Effects Regression; 10. region (hsngval = faminc) i. Options for FE model Model fe requests the fixed-effects (within) regression estimator. The command is particulary useful when an instrumental variable approach is required in particularly large datasets, because it removes the high dimensional fixed effects from the I tested with Produc data from R package plm and found the main results are the same (see the codes and outputs below). There are two packages in R that can be used for that purpose: 1)SEM 2) LAVAAN I want to model the following in R: outcome = beta Var1 + beta Var2+ beta Var1:Var2+ controls + county FE + year FE. Hi Mark: I have a similar error; however, the message I get is: Warning: estimated covariance matrix of moment conditions not of full rank. This can be specified as a matrix or as a function yielding a matrix when applied to the fitted model. Re: st: RE: ivreg versus xtivreg. Page built: 2023-02-13 using R version 4. It uses the Method of Alternating projections to sweep out multiple group effects from the normal equations before estimating the remaining coefficients with OLS. We discuss cases where the assumptions are met and violated. ) the package provides various regression diagnostics, including hat values, deletion diagnostics such as studentized residuals and 17. Note. Using the example in the Stata help file:bcuse engeldat, clear center age-twocars, prefix(z_) ivreg2h foodshare z_* (lrtotexp=) To. ) is derived from and supersedes the ivreg() function in the AER package. The only apparent difference I found is the year effect, which is caused by contrast ( xtreg sets the first year as reference, while plm directly estimates the effect for each year). , y ~ x1 + x2 | z1 + z2 + z3 , where x1 and x2 are the regressors and z1 , z2, and z3 are the instruments. frame. , show very little variation over time) may also largely get washed out by the fixed effect. at Sat Oct 19 14:03:32 CEST 2013. EDIT 2: I realised that I have the ability to interact the industry fixed effect, with either country or year. overidentification statistic not reported, and standard errors and model tests should be interpreted with caution. object, cluster=c("c")) There's an excellent post on clustering within the lm framework. frame with a list column Messages sorted by: [ date ] [ thread ] [ subject ] [ author ] Dear John Fox, Christian Kleiber, and Achim Zeileis, I am attempting to run various independent variable parameters to assess their suitability. ivreg . I'd be pleased if someone could solve my concern. In this chapter we focus on the IV regression tool called two-stage least squares (TSLS). We use "within" to specify we are using fix-effects models. 94 − 0. My model is 2sls with fixed effects but it seems there are no packages available for calculating interaction effects in R. Date. Regressors and instruments for ivreg are most easily specified in a formula with two parts on the right Instrumental variable estimation for linear models by two-stage least-squares (2SLS) regression or by robust-regression via M-estimation (2SM) or MM-estimation (2SMM). If there are only time fixed effects, the fixed effects regression model becomes Y it = β0 +β1Xit +δ2B2t+⋯+δT BT t +uit, Y i t = β 0 Supports two or more levels of fixed effects. Demean (or rather absorbe) the effect of all fixed effects on all exogenous and endogenous variables. The Fixed Effects regression model is used to estimate the effect of intrinsic characteristics of individuals in a panel data set. return results in a data. To fill this gap, I implement three recently developed tests. com ivregress performs instrumental-variables regression and weighted instrumental-variables regres-sion. Traditionally, instrumental variable analyses have been confined to linear models, in which the causal parameter of interest is typically estimated with two-stage least squares. , vcov. xi: ivreg rent pcturban i. Two-way and multi-way clustering. 2. Specifying the . You switched accounts on another tab or window. I ran a 2-stage fixed-effects panel model in R. The first sections briefly recap the general mechanics and assumptions of IV regression and show how to perform TSLS estimation using R. When you leave out the interaction, effects of each variable are estimated independently of the other. You can combine two fixed-effects with ^: e. . Bun & Teresa D. vcov. Solutions. It is essentially a wrapper for ivreg2, which must be installed for xtivreg2 to run: ssc install ivreg2, replace). Feb 6, 2019 · In other words, can I still include fixed effect with cross-section group without using dummy variable approach with xi:ivreg2 Last edited by Xiaoke Ye ; 07 Feb 2019, 01:37 . Alliance participation is not random - firms self-select (and are selected by their future partners) into alliances. xtivreg2 supports all the estimation and reporting options of ivreg2; see help ivreg2 for full descriptions and examples. The fixest package offers a family of functions to perform estimations with multiple fixed-effects in both an OLS and a GLM context. We can use a fixed-effects (FE) model to account for unobserved subject-specific characteristics. Apr 4, 2019 · I am using a fixed effects model with household fixed effects. References. Comment We would like to show you a description here but the site won’t allow us. 3. See full list on search. matrix, bread , estfun) is available and described on summary. The formula specification is a response variable followed by a four part formula. Regressors and instruments for ivreg are most easily specified in a formula with two parts on the right-hand side, e. 4 Regression with Time Fixed Effects. Bartik, Timothy J. r. May 26, 2023 · library (plm) fixed <- plm (y ~ x1, data=Panel, index=c("country", "year"), model=" within ") summary (fixed) We use index to specify the panel setting. Running the example code provided in the help page: Running the example code provided in the help page: Jun 11, 2020 · 6. 0e-09) note: variable #5 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1. These models include, among others, linear models (fit by lm and gls ), and generalized linear models (fit by glm ), for which an "eff" object Mar 21, 2022 · (dropped 83 singleton observations) note: variable #2 is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1. est store re . That Arguments. Nov 21, 2022 · The following example shows how to calculate robust standard errors for a regression model in R. The book argues that the assumption of instrument exogeneity is more likely to hold for the general sales tax (see Chapter 12. Adjust for the degrees of freedom. xtreg n w k if year>=1978 & year<=1982, re (Artificial regression overid test of fixed-vs-random effects) . In some circumstances, standard formulas are not very useful to describe a model, notably while using instrumental variable like estimators: to deal with these situations, we May 1, 2020 · remilsg May 1, 2020, 3:22pm 3. Estimation and Inference; Application to Traffic Deaths; 10. 7 Exercises; 11 Regression with a Binary Dependent Variable The principal subject of this vignette is the rationale for the extension of various standard regression diagnostics to 2SLS and the use of functions in the ivreg package to compute them, along with functions in other packages, specifically the base-R stats package (R Core Team 2020) and the car and effects packages (Fox and Weisberg 2019 Downloadable! xtivreg2 implements IV/GMM estimation of the fixed-effects and first-differences panel data models with possibly endogenous regressors. Fri, 12 Feb 2010 10:22:31 +0100. The principal subject of this vignette is the rationale for the extension of various standard regression diagnostics to 2SLS and the use of functions in the ivreg package to compute them, along with functions in other packages, specifically the base-R stats package (R Core Team 2020) and the car and effects packages (Fox and Weisberg 2019 Nov 7, 2023 · I am estimating causal effect of participation on training on employment, where participation is binary variable, outcome (employment) is binary and existence of training in a city is binary. A wide range of methods is provided for fitted ivreg model objects, including extensive functionality Random-effects linear panel-data model with outcome y, exogenous x1, and x2 instrumented by x3 using xtset data xtivreg y x1 (x2 = x3) Use fixed-effects estimator and includeindicatorsfor each level of categorical variable a xtivreg y x1 i. Previous message: [R] ivreg with fixed effect in R? Next message: [R] Extracting AICc and BIC from an ARIMA model. fixed effect, instrumental variable regression like xtivreg in stata (FE IV Dec 15, 2016 · 2. If dummy-encoding the group effects results in a manageable number of coefficients, you are probably better off by using lm(). In addition to standard regression functionality (parameter estimation, inference, predictions, etc. 0368 (overall)? Thanks! This command builds on the command reg2hdfe and ivreg2 for estimation of a linear instrumental variables regression model with two high dimensional fixed effects. If it is a function it is also employed in the two diagnostic F tests (if diagnostics = TRUE in the summary Jun 30, 2020 · Which I assume has something to do with the ivtobit package in Stata not automatically excluding those dummies like R does. subset is evaluated in the same way as variables in formula, that is first in data and then in the environment of formula. Apr 20, 2024 · The ivreg package provides a comprehensive implementation of instrumental variables regression using two-stage least-squares (2SLS) estimation. org Apr 21, 2022 · You could take a look at the very nice fixest package from L. webuse abdata (Balanced panel) . Here below is the Stata result screenshot from running the regression. Most certainly, 2SLS (here FE2SLS - fixed effects 2SLS) is possible with the plm package. it is indeed the solution, thanks for your answer ! in a case where x1 is potentially endogenous, the solution is the following: plm(y = x1 + x2 | x2 + z1, model = "within", effect = "twoways") the instruments are specified after the | sign (both exogenous explanatory variables [x2 in that case] and the nolstretch; see[R] estimation options. In fact, several models can be estimated with plm by filing the model argument. g. 'felm' is used to fit linear models with multiple group fixed effects, similarly to lm. Handle: RePEc:boc:bocode:s458530 Note: This module should be installed from within Stata by typing "ssc install ivreghdfe". reghdfe is a generalization of areg (and xtreg,fe, xtivreg,fe) for multiple levels of fixed effects (including heterogeneous slopes), alternative estimators (2sls, gmm2s, liml), and additional robust standard errors (multi-way clustering, HAC standard errors, etc). G. Feb 16, 2018 · I am able to replicate ivreg2h output for the case in which there are no fixed effects, but not for the case in which there are fixed effects ( the case in which I am interested). 7 Exercises; 11 Regression with a Binary Dependent Variable I try to put some 2SLS regression outputs generated via ivreg() from the AER package into a Latex document using the stargazer package. In the regression results table, should I report R-squared as 0. In this example x1 x 1 is a factor variable. Oct 8, 2021 · I'm trying to understand why R packages "plm" and "fixest" give me different standard errors when I'm estimating a panel model using heteroscedasticity-robust standard errors ("HC1") and state fixed effects. Notably, Instrument was also "an average of a variable at district level". Remarks and examples stata. region (hsngval = faminc) factor variables not allowed. Assuming we have a mixed-effects model of form: y = Xb + Zu + e. The easiest way to compute clustered standard errors in R is to use the modified summary function. a specification of the covariance matrix of the estimated coefficients. We do so by including the subject’s idcode in our model Jan 15, 2019 · I'm an undergraduate with very little experience in R and Econometrics, so forgive me if I mix-up my terms a little bit. May 30, 2021 · The ivreg package integrates seamlessly with other packages by providing suitable S3 methods, specifically for generic functions in the base-R stats package, and in the car, effects, lmtest, and sandwich packages, among others. What I need is to run a 2SLS regression, with two instruments for Var1, with county and year fixed effects, all weighted by county population. 2030 (within) or 0. D is endogenous and tau is exogenous, in the final equation it should be: Kelis, thanks for your interest. Bergé: R Fixest Package: IV Estimation Without Further Exogenous Variables (For the syntax with IV's). I am trying to do this simple instrumental variables estimation in R using the package systemfit and two stage least squares ( 2SLS ): y = b + b1*x1 + b2*x2 + b3*w + e. 4. Key Concept 10. 0), knitr, insight, parallel, rmarkdown, sandwich, testthat, modelsummary, ggplot2. 2 presents the generalized fixed effects We would like to show you a description here but the site won’t allow us. The ivreg package does not use any external sources. ) in the data frame. You can interact two variables using ^ with the following syntax: cluster = ~var1^var2 or cluster = "var1^var2" . l, ci. r(101); However, you can still use the xi prefix to create dummies on the fly: . The post-estimation commands functions summary and tidy. However, I would recommend that you first process the data: - Store all variables as the appropriate types (numeric, factor, etc. The syntax is similar to that in ivreg from the AER package. Calculate p-values and confidence intervals using cluster-adjusted t-statistics (based on Ibragimov and Muller (2010) , pairs cluster bootstrapped t-statistics, and wild cluster bootstrapped t-statistics (the latter two techniques based on Cameron, Gelbach, and Miller (2008) . This step is not necessary every time. First, I ran a fixed-effects plm model in which I regressed May 29, 2024 · ivreg is the high-level interface to the work-horse function ivreg. 3 Fixed Effects Regression. 94, the TSLS estimate obtained using the general sales tax as the only 10. The standard regression functionality (parameter estimation, inference, robust covariances, predictions, etc. It's hard to say what exactly goes wrong based on the information you provide. Keywords: st0514, xtqptest, xthrtest, xtistest, serial correlation, panel time series, fixed effects, higher-order serial correlation. Controlling for variables that are constant across entities but vary over time can be done by including time fixed effects. 6)Davidson and MacKinnon(1993,2004),Greene(2012, chap. Does ivreg in AER support a logit regression with instrumental variables? For example: IV = ivreg (Mort ~ Age + Sex + APACHE + PART_SendImmed + ICU_AdmImmed + ICU_LOS | Age + Sex + APACHE + PART_SendImmed + NurseOCC_Adm + NurseOCC_Disch, data = test) Where, Mort is a binary variable ICU_AdmImmed and ICU_LOS are endogenous variables, and May 18, 2021 · Fixed-effects model, not adjusting for clustered observations. Is ivprobit function in R suitable for this non-linear model or I can use ivreg? (Equivalence of xtoverid statistic and standard Hausman fixed-vs-random effects > test) . Nov 10, 2021 · 1. Examples of such intrinsic characteristics are genetics, acumen and cultural factors. ivreg rent pcturban i. s3. In the packages 1st vignette [1], you can read about the multi-part formula. fml. The fitstat function can compute all of your required tests, e. indicator variables), and it handles lots of fixed effects really really fast. regress specifies that all the covariates are to be treated as exogenous and that the Dec 24, 2018 · With AER::ivreg() and plm::plm() I can generate the same results. Regressors and instruments should be specified in a two-part formula, such as y ~ x1 + x2 | z1 + z2 + z3, where x1 and x2 are regressors and z1, z2, and z3 are instruments. di r(j) . The command ivreg does not allow factor variables: . xtoverid . 1. Our data contains repeated measures for each subject, so we have panel data in which each subject forms a group or cluster. 2 (2022-10-31 ucrt) Chapter 19 - Instrumental Variables | The Effect is a textbook that covers the basics and concepts of research design, especially as applied to causal inference from observational data. where Xb are the fixed effects and Zu are the random effects, we can extract Aug 9, 2019 · If your data are unbalanced, you will get different results from plm and Stata for the Swamy-Arora methods for random effects. You signed out in another tab or window. 6 Drunk Driving Laws and Traffic Deaths; 10. webuse hsng2, clear. r-project. fit , a set of standard methods (including print, summary, vcov, anova , hatvalues, predict, terms, model. Apr 27, 2019 · I want to interact an IV variable with a non-IV variable and be able to add fixed effects with the felm function (the library is lfe). Fernando. var2] was the 1st [resp. The goal is to find the effect of strategic alliance participation on firm performance. fml = z~x+y|fe_1^fe_2, see details. As you may know, for many fixed effects and random effects models {I should mention FE and RE from econometrics and education standpoint since the definitions in statistics are different}, you can create an equivalent SEM (Structural Equation Modeling) model. For example: fml = z~x+y. To include fixed-effects, insert them in this formula using a pipe: e. Harrison (2019) OLS and IV estimation of Feb 14, 2022 · Feb 14, 2022. I've read that variables that are highly stable (i. Suppose we have the following data frame in R that contains information on the hours studied and exam score received by 20 students in some class: Apr 20, 2024 · The ivreg package provides a comprehensive implementation of instrumental variables regression using two-stage least-squares (2SLS) estimation. and are equivalent representations of the fixed effects model (Note: \(\beta_0\) is intercept of the fixed effect model in equation 10. You can also use variables with varying slopes using square brackets Oct 28, 2020 · There are several functions from different R packages that let you do 2SLS, and they all work a little differently and have different benefits: iv_robust() from estimatr: Syntax: outcome ~ treatment | instrument; Benefits: Handles robust and clustered standard errors; ivreg() from ivreg: Syntax: outcome ~ treatment | instrument coeflegend; see[R] estimation options. I would like to instrument one variable, namely x1 x 1, present in two interaction terms. Here's some code that includes an IV and how I would manually estimate the first stage along with a double check by following into the second stage. To get useful data out of the return, you can use these data frames, you can use the resulting list directly, or you can use the generic accessor functions coef, vcov , confint, and predict. ) the package provides various regression diagnostics, including hat values This function performs two-stage least squares estimation to fit instrumental variables regression. Messages sorted by: May 28, 2024 · I'm having trouble understanding regression outputs from the ivreg function from the ivreg package in R. For example, if there is one exogenous The ivreg package has the following suggested dependencies: AER, effects (>= 4. 10. [R] ivreg with fixed effect in R? Achim Zeileis Achim. Is there a way to pull the first stage results from ivreg()?I'd like to see what the calculation looks like without running a separate regression. ac. At the time of writing of this page (February 2020), fixest is the fastest existing method to perform an object of class "ivreg" as fitted by ivreg. Example: Calculating Robust Standard Errors in R. May 29, 2020 · I'm looking for a function for interaction effects visualization which has a correspondence with ivreg or plm. May 29, 2020 · Include country and year when you include the country and year interaction. In addition to instruments I specify, ivreg uses all exogenous variables as instruments, including the dummies. s2, Estimate the 3sls using the demeaned variables. This function is intended for use with large datasets with multiple group effects of large cardinality. object <- lm(y ~ x, data = data) summary(lm. Does anyone have a hint for me? Here is the code: Subject. This model produces correct parameter estimates without creating dummy variables; however, due to the larger degrees of freedom, its standard errors and, consequently, R-squared statistic are incorrect. Reload to refresh your session. For example Jul 4, 2018 · 3. bl zr mv bt fo fm vl oj gd ha