CT = eval(form.CT2.value); // How many cell phones do you own? D = eval(form.D3.value); // In how many of the following dinosaur activities do you participate on a daily basis?
[read the newspaper,subscribe to a newspaper, use a pen/pencil, watch TV, listen to music that has ever been placed on any nondigital recordable media, recreate offline] W = eval(form.W4.value); // In how many programming languages could you design a widget of any sort? P = eval(form.P5.value); // How many of the following people have you heard of?
Linus Torvalds, Ray Ozzie, Kevin Mitnick, Jean Grey, Samwise Gamgee, Violet Blue] // Calculate values Atech = A + Math.pow(SN + CT + W + P, 2)/Math.sqrt(D + 2); // Age of Your Personal Technological Obsolescence // Output Calculated Values to Form form.Atech.value = decimalFP(Atech, 1); } // End ageTechnologyOvertakes function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function coinTossOdds(form) { // Convert Input Variables to Numeric Values N = eval(form.N0.value); // Total Number of Opportunities k = eval(form.k1.value); // Number of Times the Outcome Goes a Particular Way p = eval(form.p2.value); // Probability of Outcome Occurring in Each Opportunity [%] // Calculate values p = p/100; // Decimalized Probability q = 1 - p; // Opposite Probability probability = Factorial(N)/Factorial(k)/Factorial(N-k)*Math.pow(p, k)*Math.pow(q, N - k)*100; // Probability of the Event Occurring [%] odds = 1/(probability/100); // Odds of the Event Occurring [1 in ...] // Output Calculated Values to Form form.probability.value = decimalFP(probability, 4) + "%"; form.odds.value = decimalFP(odds, 1); } // End coinTossOdds function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function halloweenBucket(form) { // Constants Bucket = "Your Pockets Are More Than Enough"; // Default Output // Convert Input Variables to Numeric Values T = eval(form.T0.value); // Total Time You Plan to Spend Trick or Treating (in hours) A = eval(form.A1.value); // Trick or Treater's Age (If over 20, or below 0, shame on you!) Hc = eval(form.Hc2.value); // Hours Spent on Costume (If Store Bought, Take Price and Divide by 20) Pd = eval(form.Pd3.value); // Population Density of Your Targeted Neighborhood Ma = eval(form.Ma4.value); // Estimated Median Age in the Neighborhood (the lower the age, the more houses you'll likely be visiting) X = eval(form.X5.value); // Your Child's "Lust for Candy" Factor (Enter a value from 1-10, with 10 being "has strategized since last Halloween") // Calculate values B = T*(A - 0.05*A*A + Hc*Pd/Math.sqrt(Ma) + X); // Bucket Size if (B > 1) Bucket = "Your Child Should Use the Small-Size, Plastic Jack-'O-Lantern Bucket"; // Small if (B > 7) Bucket = "Your Child Should Use the Standard-Size Trick-or-Treating Bucket"; // Standard if (B > 12) Bucket = "Your Child Should Upgrade to a Pillowcase"; // Pillowcase if (B > 17) Bucket = "Your Candy Collecting Achiever Should Use a Grocery Bag"; // Grocery if (B > 25) Bucket = "Wow! You Might as Well Let Them Use a Trash Bag!"; // Trash Comment = Bucket; // Your Child's Optimum Halloween Candy Collection Container // Output Calculated Values to Form form.Comment.value = Comment; } // End halloweenBucket function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function FTRtoHMI(form) { // Convert Input Variables to Numeric Values FTC = eval(form.FTC0.value); // Total Federal Tax Receipts for Fiscal Year [billions USD] // Calculate values HMI = 255.982541*Math.pow(FTC, 0.679450); // Projected Household Median Income // Output Calculated Values to Form form.HMI.value = decimalFP(HMI, 0); } // End FTRtoHMI function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function zeroDeficitLine(form) { // Convert Input Variables to Numeric Values MHI = eval(form.MHI0.value); // Median Household Income // Calculate values FSpHH = 0.4425*MHI - 1089.59; // Federal Spending per U.S. Household // Output Calculated Values to Form form.FSpHH.value = decimalFP(FSpHH, 0); } // End zeroDeficitLine function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function incomePercentile2009(form) { // Constants earners = 211254000; // Number of Income Earners in 2009 // Convert Input Variables to Numeric Values x = eval(form.income0.value); // Your Annual Income (Total Money Income) // Calculate values maxIncome = 150000000; if(x= 1) TieTheKnot = "Yes. It's time to start shopping for a ring!"; // Comment = TieTheKnot; // The Bottom Line // Output Calculated Values to Form form.TTK.value = decimalFP(TTK, 2); form.Comment.value = Comment; } // End readyToPropose function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function topOnePctTaxCollections(form) { // Constants a = -5.3805388414261332E+06; // a b = -6.7378355944145390E-12; // b c = 5.2057116603559622E+05; // c d = 6.1169870046247370E-13; // d f= 1.1741786853311759E-01; // f g = 1.0670314607969531E-05; // g h = -4.9596727665121447E-07; // h offset = -1.1778311928168268E+05; // Offset // Convert Input Variables to Numeric Values x = eval(form.x_in0.value); // Maximum U.S. Income Tax Rate y = eval(form.y_in1.value); // Taxable Income Floor to be in Top 1% of Taxpayers // Calculate values z = (a + b*Math.exp(x) + c*Math.log(y) + d*Math.exp(x)*Math.log(y)) / (1.0 + f*x + g*y + h*x*y) + offset; // Estimated Total Tax Collections [millions U.S. dollars] // Output Calculated Values to Form form.z.value = decimalFP(z, 0); } // End topOnePctTaxCollections function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function goldCube(form) { // Constants RM = 19.3; // Density of Gold [grams per cubic centimeter] // Convert Input Variables to Numeric Values A = eval(form.A0.value); // Amount of Federal Spending [billions U.S. dollars] G = eval(form.G1.value); // Spot Price of Gold [U.S. dollars per ounce] // Calculate values RE = RM*62.428; // Convert Gold Density to Pounds per Cubic Foot P = G*16; // Convert Gold Price to Price per Pound W = A*1E9/P; // Equivalent Value in Weight of Gold [pounds] V = W/RE; // Equivalent Volume of Gold [cubic feet] S = Math.pow(V, 1/3); // Side Dimension of Gold Cube [feet] P = V/Math.pow(66.11, 3)*100; // Percent of All Gold Ever Found TEU = V/1160; // Equivalent Number of 20-feet Standard Shipping Containers // Output Calculated Values to Form form.W.value = decimalFP(W, 2); if (S > 10) { form.S.value = decimalFP(S, 1) + " x " + decimalFP(S, 1) + " x " + decimalFP(S, 1); } else { form.S.value = decimalFP(S, 2) + " x " + decimalFP(S, 2) + " x " + decimalFP(S, 2); } form.P.value = decimalFP(P, 4) + "%"; form.TEU.value = decimalFP(TEU, 1); } // End goldCube function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function howManyKids(form) { // Constants O = "No. You're not ready yet!"; // Default Response // Convert Input Variables to Numeric Values S = eval(form.S0.value); // Your combined household salary K = eval(form.K1.value); // Combined, how many brothers and sisters do you and your spouse have (include yourselves in this number) T = eval(form.T2.value); // Combined hours per week you and your significant other work outside the house A = eval(form.A3.value); // On a scale from 1-10, the highest level of aversion you have to any of the following: Changing diapers, sleep deprivation, visiting in-laws, tantrums E = eval(form.E4.value); // On a scale from 1-10, how concerned are you about global overpopulation // Calculate values if (S >= 30000) { K = Math.pow((S - 30000)/5000, 1/3) + (K + 11 - E)/(T/20 + A); // Number of Kids } else { K = -Math.pow((30000 - S)/5000, 1/3) + (K + 11 - E)/(T/20 + A); // Number of Kids; } if (K >= 1) O = "You're probably ready!"; // Should You Have Kids? shouldYou = O; // Should You Have Kids? Kids = K; // How Many Kids Should You Have? C = "No - we just provide that to give you an idea of how close you might be to a particular 'whole child' threshold so you can play with tweaking your input data!"; // Should You Be Concerned by the Decimal Portion of the Answer? // Output Calculated Values to Form form.shouldYou.value = shouldYou; form.Kids.value = decimalFP(Kids, 1); form.C.value = C; } // End howManyKids function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function gasPriceToUnemploymentRate(form) { // Constants CPIJan2011 = 220.223; // Consumer Price Index, January 2011 // Convert Input Variables to Numeric Values Gnominal = eval(form.Gnominal0.value); // Average Price of a Gallon of Gasoline CPILatest = eval(form.CPILatest1.value); // Most Recent Consumer Price Index (CPI-U) Value // Calculate values Greal = CPIJan2011/CPILatest*Gnominal; // Adjust Gasoline Price to be in Constant January 2011 U.S. Dollars UE50 = 1.92*Gnominal + 2.024; // Projected Unemployment Rate // Output Calculated Values to Form form.UE50.value = decimalFP(UE50, 1) + "%"; } // End gasPriceToUnemploymentRate function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function planetValue(form) { // Constants Msun = 1.9891; // Mass of the Sun Mearth = 5.9736; // Mass of the Planet Earth Mmars = 0.64585; // Mass of the Planet Mars Tearth = 254.3; // Effective Temperature Tmars = 210.2; // Effective Temperature // Convert Input Variables to Numeric Values Teff = eval(form.Teff0.value); // Effective Temperature of the Planet [degrees Kelvin] Mplanet = eval(form.Mplanet1.value); // Mass of the Planet [quadrillion kg] Tyr = eval(form.Tyr2.value); // Year of Discovery [Enter 2009 if Discovered Prior to 2009] Tstar = eval(form.Tstar3.value); // Age of the Planet's Star [billion years] Mstar = eval(form.Mstar4.value); // Mass of the Planet's Star [quintillion kg] Vstar = eval(form.Vstar5.value); // Apparent Visual Magnitude (Brightness) of the Planet's Star // Calculate values V1 = 6000000*Tstar/0.5 * Math.pow(Msun/Mstar, 1/3); V2 = Math.exp(-Math.pow(Math.log(Mplanet/Mearth)/Math.LN10/0.2, 2)); V3 = Math.exp(-Math.pow((Teff - 273)/30, 2)); V4 = Math.exp(-((Math.max(Tyr, 2009) - 2009)/4)); V5 = Math.sqrt(Math.pow(2.5, 12-Vstar)); V = V1*V2*V3*V4*V5; // Estimated Value [Constant 2009 U.S. Dollars] // Output Calculated Values to Form form.V.value = decimalFP(V, 2); } // End planetValue function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function lightTechnologyComparison(form) { // This function will find out if one electric light source type is more // economical than a competing technology // Convert Input Variables to Numeric Values C = eval(form.C0.value); // Electricity Rate [$ per kiloWatt-hour] H = eval(form.H1.value); // Time Period of Operation [Hours] L1 = eval(form.L12.value); // Technology for Light #1 [Incandescent, Fluorescent, LED = 1, CFL = 2/3] L2 = eval(form.L23.value); // Technology for Light #2 [Incandescent, Fluorescent, LED = 1, CFL = 2/3] W1 = eval(form.W14.value); // Light #1 Power Consumption Rate [Watts] W2 = eval(form.W25.value); // Light #2 Power Consumption Rate [Watts] T1 = eval(form.T16.value); // Rated Life of Light #1 [Hours] T2 = eval(form.T27.value); // Rated Life of Light #2 [Hours] P1 = eval(form.P18.value); // Purchase Price of Light #1 [$ per Lamp] P2 = eval(form.P29.value); // Purchase Price of Light #2 [$ per Lamp] // Calculate values N1 = Math.ceil(H/T1/L1); // Number of Consumed Units Like Light #1 N2 = Math.ceil(H/T2/L2); // Number of Consumed Units Like Light #1 CB1 = N1*P1; // Cost of Bulbs OVer Time Period of Operation for Light #1 CB2 = N2*P2; // Cost of Bulbs Over Time Period of Operation for Light #2 CE1 = H*W1/1000*C; // Cost of Electricity Over Time Period of Operation for Light #1 CE2 = H*W2/1000*C; // Cost of Electricity Over Time Period of Operation for Light #2 CT1 = CB1 + CE1; // Total Cost of Ownership and Use of Light #1 CT2 = CB2 + CE2; // Total Cost of Ownership and Use of Light #2 if(CT10) IPM = "+"; G = -I*2.65; // Effective Change in GDP Growth Rate if (G>0) GPM = "+"; // Output Calculated Values to Form form.I.value = IPM + decimalFP(I, 1) + "%"; form.G.value = GPM + decimalFP(G, 1) + "%"; } // End cdsGDP function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function perfectToast(form) { // Convert Input Variables to Numeric Values ha = eval(form.ha0.value); // Bread Thickness [millimeters] Cpa = eval(form.Cpa1.value); // Bread Specific Heat [kJ/kg/oC] Cpb = eval(form.Cpb2.value); // Butter Specific Heat [kJ/kg/oC] pa = eval(form.pa3.value); // Density of Bread [g/L] pb = eval(form.pb4.value); // Density of Butter [g/L] T = eval(form.T5.value); // Temperature of Bread Immediately After Toasting [oC] wa = eval(form.wa6.value); // Weight of Bread Slice [g] // Calculate values hb = (Cpa*pa*(T-35))/60/Cpb/pb*ha; // Thickness of Butter [mm] F = Cpa*(T-35)/60/Cpb*wa; // Weight of Butter [g] // Output Calculated Values to Form form.hb.value = decimalFP(hb, 2); form.F.value = decimalFP(F, 2); } // End perfectToast function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function actuarialssIRR2010(form) { // This function will return an approximate internal rate of return for average // Social Security old age beneficiaries under present law (August 2011). The // formula was generated using ZunZun's 3-D contour mapping functions, with x // representing the difference between the individual's birth year and 1913, y // representing the individual's average lifetime annual income in 2010 dollars. // ZunZun generated the various values for the constants a, b, and c. // // Reference Link: http://www.ssa.gov/OACT/NOTES/ran5/an2009-5.html // Convert Input Variables to Numeric Values by = eval(form.by0.value); // Your Birth Year ai = eval(form.ai1.value); // Your Average Lifetime Annual Income hh = eval(form.hh2.value); // Household Type // Calculate values x = by - 0 // Difference Between Birth Year and 1913 // Set Constants if (hh == 0) { // Single Male a = 3.4830058483131051E+07; b = -1.3769406994404348E+07; c = -9.8160827145620715E+01; d = 1.8145060082775326E+06; f = 9.3514340906403959E+00; g = -7.9703860850292258E+04; h = -3.0071162991225719E-01; } if (hh == 1) { // Single Female a = 4.6465115514614679E+07; b = -1.8370376588547118E+07; c = -9.6139752013958059E+01; d = 2.4209750412252117E+06; f = 9.1590634707827121E+00; g = -1.0635075353067368E+05; h = -2.9447480291128159E-01; } if (hh == 2) { // One-Earner Couple a = 4.9682508087921910E+07; b = -1.9637628433339857E+07; c = -1.0157001107651740E+02; d = 2.5873554737905581E+06; f = 9.6840790377464145E+00; g = -1.1363222687139083E+05; h = -3.1141287088394165E-01; } if (hh == 3) { // Two-Earner Couple a = 4.3581663567176104E+07; b = -1.7228949575518753E+07; c = -9.9209529911546269E+01; d = 2.2703632689268854E+06; f = 9.4518688353709877E+00; g = -9.9726351340780966E+04; h = -3.0402682162821293E-01; } // Approximated Internal Rates of Return from Social Security IRR = a; IRR += b*Math.log(x); IRR += c*Math.log(ai); IRR += d*Math.pow(Math.log(x), 2); IRR += f*Math.pow(Math.log(ai), 2); IRR += g*Math.pow(Math.log(x), 3); IRR += h*Math.pow(Math.log(ai), 3); LIRR = IRR - .20; // Low Rate of Return Approximation (%) AIRR = IRR; // Average Rate of Return Approximation (%) HIRR = IRR + .20; // High Rate of Return Approximation (%) // Output Calculated Values to Form form.LIRR.value = decimalFP(LIRR, 2); form.AIRR.value = decimalFP(AIRR, 2); form.HIRR.value = decimalFP(HIRR, 2); } // End actuarialssIRR2010 function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function generalLogistic(A, C, M, B, T, x) { return A + C/Math.pow(1 + T*Math.exp(-1*B*(x - M)) , 1/T); } // End generalLogistic function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function indIncPctle2010(form) { // Constants earners = 211492000; // Number of Income Earners in 2010 PA = 3.3449980649281133E-02; PB = 1.3146441528199077E+01; PC = 1.1910731880657568E+01; PD = 9.9781767595278037E-01; PE = 5.4858345499794581E+00; // Convert Input Variables to Numeric Values x = eval(form.income0.value); // Your Annual Total Money Income // Calculate values percentile = PD + (PA-PD) / Math.pow(1.0 + Math.pow(Math.log(x)/PC, PB), PE); percentile = Math.max(percentile, 0); // Set floor for income percentile percentile = Math.min(percentile, 1); // Set ceiling for income percentile earnLess = percentile*earners; // Approximate Number of Americans Earning Less earnMore = earners - earnLess; // Approximate Number of Americans Earning More percentile *= 100; // Output Calculated Values to Form form.percentile.value = decimalFP(percentile, 1); form.earnLess.value = decimalFP(earnLess, 0); form.earnMore.value = decimalFP(earnMore, 0); } // End indIncPctle2010 function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function hhIncPctle2010(form) { // Constants households = 118682000; // Number of U.S. Households in 2010 HA = 7.0540066417813362E-03; HB = 1.3667304099403975E+01; HC = 1.3615445184767367E+01; HD = 9.9878358756931840E-01; HE = 1.6539706906092988E+01; // Convert Input Variables to Numeric Values x = eval(form.income0.value); // Your Annual Household Total Money Income // Calculate values percentile = HD + (HA-HD) / Math.pow(1.0 + Math.pow(Math.log(x)/HC, HB), HE); percentile = Math.max(percentile, 0); // Set floor for income percentile percentile = Math.min(percentile, 1); // Set ceiling for income percentile earnLess = percentile*households; // Approximate Number of Americans Earning Less earnMore = households - earnLess; // Approximate Number of Americans Earning More percentile *= 100; // Output Calculated Values to Form form.percentile.value = decimalFP(percentile, 1); form.earnLess.value = decimalFP(earnLess, 0); form.earnMore.value = decimalFP(earnMore, 0); } // End hhIncPctle2010 function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function wrongPath2010(form) { // Convert Input Variables to Numeric Values x = eval(form.x0.value); // Median Household Income // Calculate values y = 311420.423287*Math.pow(x, 1.463074); // Estimated Amount of Money Collected by U.S. Government // Output Calculated Values to Form form.y.value = decimalFP(y, 0); } // End wrongPath2010 function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function flatTax2010(form) { // Set Constants tEX2009 = 284239508; // Total Exemptions Claimed in 2009 - Most Recent Data Available (http://www.irs.gov/pub/irs-soi/09intba.xls) cTC2010 = 898549000000; // Cumulative Personal Income Tax Collections for 2010 (http://www.gpoaccess.gov/usbudget/fy12/xls/BUDGET-2012-TAB-2-1.xls) GDP2010 = 14526500000000; // 2010 U.S. GDP (http://www.bea.gov/newsreleases/national/gdp/2011/txt/gdp2q11_2nd.txt) num2010 = 118682000; // Number of Households in 2010 // Income Distribution Constants A2010 = -1.3088145248973815E+03; C2010 = 1.2014608613920317E+05; M2010 = 1.1048130487672319E+01; B2010 = 2.6414531291200865E+00; T2010 = 2.5357700309477940E+00; // Code Reference Constants i = 0; // Counting Variable sAI = 0; // Sum of Aggregate Income inc = 10000; // Income Increment cap = 150000000; // Maximum Value for Income Distribution // Convert Input Variables to Numeric Values tax = eval(form.tax0.value)/100; // Flat Percentage Income Tax Rate itc = eval(form.itc1.value); // Value of Individual Tax Credit tmi = eval(form.tmi2.value); // Your Household Annual Total Money Income num = eval(form.num3.value); // Number of Individuals Covered by Income Reported on Your Tax Return // Individual Income Tax Calculations iit = tmi*tax; // Individual Income Tax [$] iic = itc*num; // Value of Individual Tax Credits [$] tpc = iit - iic; // Net Individual Income Taxes, Post Credits if (tpc = -1)) { var mainMessage =" Merry Christmas!!! "; var speed=175; var scrollingRegion=100; var tempLoc=(scrollingRegion*3/mainMessage.length)+1; if (tempLocscrollingRegion) startPosition=0; setTimeout("Xmascountdown()",speed); } else { if (days >= 0) { var theDay = XmasDate; } else { var theDay = new Date(XmasDate.getYear()+1,XmasDate.getMonth(),XmasDate.getDate()); } var second = Math.floor((theDay.getTime() - today.getTime())/1000); var minute = Math.floor(second/60); var hour = Math.floor(minute/60); var day = Math.floor(hour/24); CDay= day; CHour= hour % 24; CMinute= minute % 60; CSecond= second % 60; dayOrDays = " days, "; hourOrHours = " hours, "; minuteOrMinutes = " minutes and "; secondOrSeconds = " seconds"; if (CDay 0) dayOrDays = " day, "; if (CHour 0) hourOrHours = " hour, "; if (CMinute 0) minuteOrMinutes = " minute and "; if (CSecond 0) secondOrSeconds = " second"; var DayTill = CDay + dayOrDays + CHour + hourOrHours + CMinute + minuteOrMinutes + CSecond + secondOrSeconds; clock.XmascountdownDisplay.value = DayTill; var counter = setTimeout("Xmascountdown()", 1000); } } // End Xmascountdown function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function volPriceAbort2008(form) { // Convert Input Variables to Numeric Values C = eval(form.C0.value); // Annual Caseload // Calculate values P = 350.37*(1 - Math.exp(-4.72*Math.pow((Math.max(C,30) - 28.22), -0.44))) + 412.45; // Average Price Paid for Abortion, 2008 R = C*P; // Estimated Annual Revenue for Abortion Provider // Output Calculated Values to Form form.P.value = decimalFP(P, 2); form.R.value = decimalFP(R, 2); } // End volPriceAbort2008 function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function accountingManipulations2010(form) { // This function differs from the original accountingManipulations function in that it incorporates // soft assets into the overall F-score calculation, the formula for which was modified in a 21 April 2010 // revision to the original paper "Predicting Material Accounting Misstatements". // Constants KNOWN = 494; // Number of Known Manipulating Firms-Years in Authors' Sample NONMAN = 133461; // Number of Non-Manipulating Firms-Years in Authors' Sample // F-Score Coefficients A = -7.893; B = 0.790; C = 2.518; D = 1.191; E = 1.979; F = 0.171; G = -0.932; H = 1.029; // Initial Default Values issue = 0; // Indicates firm has not issued new long-term debt, common stock, or preferred stock. // Convert Input Variables to Numeric Values // Note: Variable Naming Convention is based on Compustat Data Reference and Number of Years prior to the Year of Interest // i.e. Data 6 (Total Assets) is D06, one year prior to year of interest is Y1, resulting variable is: D06Y1 // D12Y0 = eval(form.D12Y00.value); // Sales (Revenues) - Year of Interest D12Y1 = eval(form.D12Y10.value); // Sales (Revenues) - One Year Prior D18Y0 = eval(form.D18Y01.value); // Net Income Before Extraordinary Items or Cumulative Effect of Accounting Changes - Year of Interest D18Y1 = eval(form.D18Y11.value); // Net Income Before Extraordinary Items or Cumulative Effect of Accounting Changes - One Year Prior D01Y0 = eval(form.D01Y02.value); // Cash and Cash Equivalents - Year of Interest D01Y1 = eval(form.D01Y12.value); // Cash and Cash Equivalents - One Year Prior D01Y0A = eval(form.D01Y0A3.value); // Short Term Investments - Year of Interest D01Y1A = eval(form.D01Y1A3.value); // Short Term Investments - One Year Prior D02Y0 = eval(form.D02Y04.value); // Receivables (Total) - Year of Interest D02Y1 = eval(form.D02Y14.value); // Receivables (Total) - One Year Prior D02Y2 = eval(form.D02Y24.value); // Receivables (Total) - Two Years Prior D03Y0 = eval(form.D03Y05.value); // Inventories (Total) - Year of Interest D03Y1 = eval(form.D03Y15.value); // Inventories (Total) - One Year Prior D06Y0 = eval(form.D06Y06.value); // Total Assets - Year of Interest D06Y1 = eval(form.D06Y16.value); // Total Assets - One Year Prior D06Y2 = eval(form.D06Y26.value); // Total Assets - Two Years Prior D08Y0 = eval(form.D08Y0.value); // Property, Plant and Equipment (Total - Net) - Year of Interest D130Y0 = eval(form.D130Y07.value); // Preferred Stock (Total) - Year of Interest D130Y1 = eval(form.D130Y17.value); // Preferred Stock (Total) - One Year Prior D216Y0 = eval(form.D216Y08.value); // Total Shareholder's (or Owner's) Equity - Year of Interest D216Y1 = eval(form.D216Y18.value); // Total Shareholder's (or Owner's) Equity - One Year Prior D111Y0 = eval(form.D111Y09.value); // Issuance of Long-Term Debt - Year of Interest D108Y0 = eval(form.D108Y0X.value); // Issuance of Common or Preferred Stock - Year of Interest // Calculate values UnProb = KNOWN/NONMAN; // Unconditional Probability of Accounting Manipulation ATAY0 = (D06Y0 + D06Y1)/2; // Average Total Assets Between Year[t] and Year[t-1] ATAY1 = (D06Y1 + D06Y2)/2; // Average Total Assets Between Year[t-1] and Year[t-2] CRY0 = D02Y0 - D02Y1; // Change in Receivables Between Year[t] and Year[t-1] CRY1 = D02Y1 - D02Y2; // Change in Receivables Between Year[t-1] and Year[t-2] CIY0 = D03Y0 - D03Y1; // Change in Inventories Between Year[t] and Year[t-1] if (D111Y0 > 0) issue = 1; // Firm Issued Long Term Debt in Year of Interest if (D108Y0 > 0) issue = 1; // Firm Issued Common or Preferred Stock in Year of Interest ch_earn = D18Y0/ATAY0 - D18Y1/ATAY1; // Change in Earnings ch_cs = (D12Y0 - CRY0)/(D12Y1 - CRY1) - 1; // Change in Cash Sales ch_inv = CIY0/ATAY0; // Change in Inventories soft_assets = (D06Y0 - D08Y0 - D01Y0)/D06Y0; // Percentage of Soft Assets ch_rec = CRY0/ATAY0; // Change in Receivables rsst_acc = ((D216Y0-(D01Y0+D01Y0A)-D130Y0) - (D216Y1-(D01Y1+D01Y1A)-D130Y1))/ATAY0; // RSST Accruals formula = A + B*rsst_acc + C*ch_rec + D*ch_inv + E*soft_assets + F*ch_cs + G*ch_earn + H*issue; // Mathematical Model acct_Pr = Math.exp(formula)/(1 - Math.exp(formula)); // Probability of Accounting Manipulation FScore = acct_Pr/UnProb; // F-Score // Output Calculated Values to Form form.FScore.value = decimalFP(FScore, 2); } // End accountingManipulations2010 function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function millionaireDecayFunction(form) { // Constant Values a = 1.4023522734010808E+02; b = 2.5861045923015835E+00; c = 6.1510275142758608E-01; Offset = -4.0228809113431126E+01; // Convert Input Variables to Numeric Values x = eval(form.x0.value); // Number of Years After Having Earned $1 Million // Calculate values y = Math.max(a / (1.0 + Math.pow(x/b, c)) + Offset, 0); // Odds of Still Earning $1 Million After Entered Number of Years // Output Calculated Values to Form form.y.value = decimalFP(y, 1) + "%"; } // End millionaireDecayFunction function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function billionaireDecayFunction(form) { // Constants p1 = 1.27718984563; // a p2 = 0.25921297855; // b p3 = 82.73165076970; // c p4 = 0.00000001351; // d p5 = -2.14385748741; // e Offset = 0.22578156607; // f // Convert Input Variables to Numeric Values v = eval(form.v0.value); // Number of Years After Becoming a Top 400 Taxpayer // Calculate values g = p3/(1+Math.exp((v-p1)/p2)) + p4*Math.exp((v-45)/p5) + Offset; // Probability of Being a Top 400 Taxpayer After Entered Number of Years // Output Calculated Values to Form form.g.value = decimalFP(g, 2) + "%"; } // End billionaireDecayFunction function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function celebrityMarriageOdds(form) { // Convert Input Variables to Numeric Values NYT = eval(form.NYT0.value); // "Good" Fame: Number of search results since 1990 in New York Times archives ENQ = eval(form.ENQ1.value); // "Bad" Fame: Number of search results since 1990 in National Enquirer archives Ah = eval(form.Ah2.value); // Husband's Age Aw = eval(form.Aw3.value); // Wife's Age Sc = eval(form.Sc4.value); // Overexposure: Number of scantily-clad photos among the top five photos returned in a Google image search for the wife's name Md = eval(form.Md5.value); // Dating: Number of months the celebrity couple dated before getting married. T = eval(form.T6.value); // Time: Years after getting married for which to calculate the percentage odds that the couple will still be married. // Calculate values if(NYT==24 && ENQ==23 && Ah==29 && Aw==24 && Sc==0 && Md==6 && T==50) { data = "Default"; } else { data = "0"; } FR = NYT/ENQ; // "Good" to "Bad" Fame Ratio ADER = (Ah + Aw)/(Sc + 5); // Age Disparity/Exposure Ratio DDF = Md*Math.pow(Md/(Md + 2), Math.pow(T, 2)); // Dating Duration Factor C = 50*Math.pow(FR*ADER*DDF, 1/15); // Percentage Chance of Still Being Married After Entered Number of Years // Output Calculated Values to Form form.FR.value = decimalFP(FR, 1); if (data==0) { form.C.value = decimalFP(C, 1) + "%"; } else { form.C.value = decimalFP(C, 15) + "%"; } } // End celebrityMarriageOdds function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function whiteheadOilQuantityChange(form) { // Convert Input Variables to Numeric Values Q = eval(form.Q0.value); // Daily Oil Production Data dP = eval(form.dP.value); // Change in Price P = eval(form.P2.value); // Current Oil Price (per Barrel) ed = eval(form.ed3.value); // Demand Elasticity es = eval(form.es4.value); // Supply Elasticity // Calculate values dQ = -dP*(-ed + es)*Q/(P-dP); // Estimated Change in Quantity of Oil // Output Calculated Values to Form form.F.value = decimalFP(dQ, 0); } // End whiteheadOilQuantityChange function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function odds100(form) { // Convert Input Variables to Numeric Values x = eval(form.x0.value); // Your Current Age xxx = eval(form.xxx1.value); // Your Gender // Calculate percentage odds switch(xxx) { case 0: // NIST Lanczos a = 1.8914210628779582E-17; b = -3.8393903895747944E-01; c = -2.5649393951533865E-02; d = 9.2332838945229062E-02; f = 2.8567058898200470E-01; g = 1.8240274567965394E-02; y = a*Math.exp(-b*x) + c*Math.exp(-d*x) + f*Math.exp(-g*x); break; case 1: // Cellular Conductance with Offset p1 = 1.2122071117924841E+02; p2 = 2.7365970886805648E+00; p3 = -2.1031903122574354E+03; p4 = 3.7393387502800068E-01; p5 = -1.3030458899563473E+02; Offset = 2.1030023289651485E+03; y = p3/(1+Math.exp((x-p1)/p2)) + p4*Math.exp((x-45)/p5) + Offset; break; } // End switch statement. // Calculate values p100 = y*100; // Percentage Chance of Reaching Age 100 if (x>=100) p100 = "100"; // Output Calculated Values to Form form.p100.value = decimalFP(p100, 1) + "%"; } // End odds100 function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function charityTaxDeductionValue(form) { // Convert Input Variables to Numeric Values C = eval(form.C0.value); // Amount Donated to Charity [$] T = eval(form.T1.value); // Your Marginal Tax Bracket [%] // Calculate values R = T/100; // Decimalized Tax Rate V = C*R; // Tax Value of Your Charitable Donations // Output Calculated Values to Form form.V.value = decimalFP(V, 2); } // End charityTaxDeductionValue function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function happinessQuantified(form) { // Convert Input Variables to Numeric Values P1 = eval(form.P10.value); P2 = eval(form.P21.value); E = eval(form.E2.value); H = eval(form.H3.value); // Calculate values HAPPY = (P1 + P2) + 5*E + 3*H; // Your Personal Happiness Level // Output Calculated Values to Form form.HAPPY.value = decimalFP(HAPPY, 1); } // End happinessQuantified function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function caloriesWalk(form) { // Constants Burn = 262; // Average Calories Burned per Hour Walking (160 lb person) // Convert Input Variables to Numeric Values Calories = eval(form.Calories0.value); // Calories // Calculate values Time = Calories/Burn; // Time Hours = Math.floor(Time); // Hours Minutes = Math.floor((Time - Hours)*60); // Minutes OUTPUT = Hours + " hours and " + Minutes + " minutes"; // Approximate Time // Output Calculated Values to Form form.OUTPUT.value = OUTPUT; } // End caloriesWalk function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function hamiltonBrent2Pump(form) { // Convert Input Variables to Numeric Values B = eval(form.B0.value); // Price per Barrel of Brent Crude Oil // Calculate values P = 0.839 + 0.02499*B; // Average U.S. Price per Gallon // Output Calculated Values to Form form.P.value = decimalFP(P, 2); } // End hamiltonBrent2Pump function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function cumulativeOdds(form) { // Constants offenderTake = 7085.91; // Average Take per Offender in U.S. in 2011 // Convert Input Variables to Numeric Values successRate = eval(form.successRate0.value); // Success Rate of Bank Crimes [%] numberCrimes = eval(form.numberCrimes1.value); // Number of Bank Crimes You'll Attempt // Calculate values s = successRate/100; // Decimalized Percentage Odds Odds = Math.pow(s, numberCrimes)*100; // The Odds That You'll Succeed In That Many Bank Crimes Take = offenderTake * numberCrimes; // Your Estimated "Take" from All Your Bank Crimes // Output Calculated Values to Form form.Odds.value = decimalFP(Odds, 1) + "%"; form.Take.value = "$" + decimalFP(Take, 2); } // End cumulativeOdds function. // //-------|---------|---------|---------|---------|---------|---------|---------| // function safeIndex(form) { // Convert Input Variables to Numeric Values N = eval(form.N0.value); // Estimated Population in Known Rage MVP = eval(form.MVP1.value); // Minimum Viable Population // Calculate values SAFE = Math.log(N)/Math.LN10 - Math.log(MVP)/Math.LN10; // SAFE Index Score // Output Calculated Values to Form form.SAFE.value = decimalFP(SAFE, 2); } // End safeIndex function. // //-------|---------|---------|---------|---------|---------|---------|---------| // // //-------|---------|---------|---------|---------|---------|---------|---------| // -->
Political Calculations
Unexpectedly Intriguing!
07 August 2026
Some inventions are so old that we don't know the names of their inventors. Handaxes made from stone. The bow and arrow. Bricks. The wheel.
Well, maybe not the wheel, because we do know the name of its inventor! The wheel was invented by John Keogh, who was awarded Australian Innovation Patent 2001100012 for its invention in May 2001.
We're not making this up! Here's a colorized version of Figure 2 from the patent, which clearly depicts Keogh's innovation:
Here is the portion of the Keogh's patent that describes his invention, which certainly matches what we've come to know as the wheel:
The invention relates to a device for facilitating transport of goods and persons. In particular, the device relates to a circular object which enables such goods and persons to be held above a surface and simultaneously moved with respect to the surface approximately parallel thereto.
The background of the invention describes the problem Keogh's wheel solves:
In the past, transportation of goods and persons has been conducted in a number of ways. The predominant means has been transport of persons on foot, and carrying thereby of goods requiring transport.
Other means of transport have included, in colder climates, skis, sleds, toboggans and the like, which slide over a smooth (low coefficient of friction) surface such as ice or snow, thus transporting the person and/or goods. These modes of transport have the advantage that when travelling down a sloped surface, free movement, that is, unassisted forward motion, is possible. The user is only required to apply effort to cause movement when travelling uphill or on a substantially flat plane, and this reduced effort helps the user move to the desired destination more quickly and more easily.
Unfortunately, such smooth surfaces for sliding over are not generally available in warmer climates where snow and ice do not form naturally. As such, and in the absence of alternatives, foot transport may be required. It would be useful if a device was available which enabled such unassisted forward motion on downhill slopes on surfaces having a much higher coefficient of friction than snow or ice.
It's hard to believe that such a useful device has only existed as a patented invention since May 2001. But if you've made it this far, you're probably thinking there's something more to this story than the invention of the wheel.
You would be right! Matthew Rimmer's 2025 book Sub-patent Innovation Rights: Utility Models, Petty Patents and Innovation Patents Around the World tells the real story behind Keogh's successfully patented invention:
In 2001, a patent attorney called John Keogh was issued an innovation patent by IP Australia for a ‘circular transportation facilitation device’. There were also patent claims relating to rubber wheels and tires. The field of the invention was a ‘device for facilitating transport of goods and persons’. The background explained that a ‘circular transportation facilitation device’ would be an improvement on walking, and on other devices, like ‘skis, sleds, toboggans and the like’. The application was accompanied by an illustration of a wheel.
There was also a perspective drawing of a cart incorporating ‘a series of circular transportation facilitation devices in accordance with a preferred aspect of the present invention.’
Keough said that he patented the wheel in order to establish that the innovation patent system was flawed because it did not need to be examined by the patent office. He explained his concerns:
The patent office would be required to issue a patent for anything. All they’re doing is putting a rubber stamp on it. The impetus came from the Federal Government. Their constituents claimed the cost of obtaining a patent was too high so the government decided to find a way to issue a patent more easily.
Keogh noted that he had no immediate plans to patent fire, crop rotation, or other fundamental advances in civilization. John Keogh had previously written about the dangers of innovation patents, warning: ‘These junk patents may bring the entire Australian patent system into disrepute’.
Keough succeeded far beyond what he might have hoped. The Australian Patent Office was forced to recognize the deficiencies in their practices that were exposed by Keogh's patent. On 30 August 2001, the Keogh's patent was revoked. It would take another 20 years however before Australia's government learned the lesson it should have and finally abolished the country's second-tier innovation patent scheme. Australia's IP Office officially phased out its innovation patent system on 26 August 2021.
Even so, Keogh's patent for the wheel represents a true achievement. Both Keogh and the Australian Patent Office were jointly awarded an Ig-Nobel Prize in 2001 for their accomplishment.
The wheel is an amazing invention. But the story of its 2001 reinvention is just as amazing.
From the Inventions in Everything Archives
The IIE team has previously covered one other example of an invention whose true purpose was to expose problems in how patents are awarded:
Labels: technology
06 August 2026
The average mortgage payment on the typical new home sold in the U.S. rose above the upper limit of affordability for the typical American household in May 2026.
The change comes eight months after the affordability of the median new home had finally become affordable for households earning the median household income for the first time since March 2022. A combination of rising mortgage rates and rising new home prices are responsible for the development. Both have increased since bottoming at their most affordable levels in years in March 2026.
Here are the three numbers that define how affordable a new home is for the typical American household:
- Median new home sale price: $424,900
- Median household income: $87,646
- Average 30-year conventional fixed mortgage rate: 6.44%
Median household income also increased during this time, but not by enough to offset the impact of the other two factors. For a household at the exact middle of the U.S. income spectrum, the average mortgage payment for a new home purchased at the national median sale price with zero-percent down consumed 36.6% of the household's monthly income in May 2026.
This value is higher than the upper threshold of affordability defined by the 28/36 rule that mortgage lenders traditionally use to determine whether to extend a mortgage to new home buyers. A monthly mortgage payment that consumes more than 36% of a household's income means that the median new home sold in May 2026 is outside the affordable reach of a household earning the median income, even if it has no other debts.
The following chart shows how May 2026's level of relative affordability for new homes compares with the affordability for every month since January 2000:
Looking forward, the average interest rate for a 30-year conventional fixed rate mortgage increased to 6.49% in June 2026. This increase creates additional headwinds for new home affordability in the United States.
References
U.S. Census Bureau. New Residential Sales Historical Data. Houses Sold. [Excel Spreadsheet]. Accessed 24 July 2026.
U.S. Census Bureau. New Residential Sales Historical Data. Median and Average Sale Price of Houses Sold. [Excel Spreadsheet]. Accessed 24 July 2026.
Freddie Mac. 30-Year Fixed Rate Mortgages Since 1971. [Online Database]. Accessed 1 August 2026. Note: Starting from December 2022, the estimated monthly mortgage rate is taken as the average of weekly 30-year conventional mortgage rates recorded during the calendar month.
Image Credit: Microsoft Bing Image Generator. Prompt: "An editorial cartoon of an American family looking sadly at a new house with a "For Sale" sign in front of it that they cannot afford." We modified the generated image to add text to the label on the "For Sale" sign.
Labels: real estate
05 August 2026
Two months ago, the S&P 500 (Index: SPX) was rising so quickly it raised the prospect the index could see a break down in the relative period of order the index established since the end of 2023.
Instead, after peaking on 2 June 2026, the S&P 500 has reverted toward its established mean trajectory. Through the end of July 2026, the index is hovering right around that 31-month-old central trend curve.
Which is to say the index remains well within its established relative period of order after having regressed toward its mean trend trajectory. Whatever bubble might have been forming within the index has mostly deflated.
The following chart visualizes the relationship between the value of the S&P 500 and its underlying trailing year dividends per share from 29 December 2023 through 31 July 2026:
Previously on Political Calculations
- How Big is the AI Bubble and Is It Really a Bubble?
- The Definition of a Bubble
- The Ultimate Sell Signal
- What Caused the Dot Com Bubble to Begin and What Caused It to End?
- The Black Monday Stock Market Crash Explained
- Not Necessarily Wrong But Useful
Image Credit: Microsoft Copilot Designer. Prompt: "An editorial cartoon of a Wall Street bull and bear looking at a balloon labeled 'AI BUBBLE?' that has deflated".
Labels: chaos, data visualization, dividends, SP 500
04 August 2026
Motio Research's initial estimate of U.S. median household income for June 2026 is $88,110, a $370 (or 0.4%) decrease from the firm's initial estimate of $88,480 for May 2026.
Here are screenshots of the interactive charts Motio Research provides to visualize trends in the U.S.' median household income. The first chart presents the firm's Household Income Index, which is based on a three-month moving average that sets the period of January 2010 through March 2010 at a value of 100. The second chart presents their monthly median household income estimates in nominal (not adjusted for inflation) terms for the period from January 2010 through June 2026.
Monthly Household Income Index
Median Household Income Estimates
Motio Research offered the following analysis of the month-over-month decline in their survey-based median household income estimate:
The U.S. Real Median Household Income Index fell to 118.9. Nominal median household income also declined, falling 0.3% to $88,110. The real estimates are expressed in June 2026 dollars using Chained CPI-U; the series are seasonally adjusted three-month averages, and the index is set to 100 in March 2010.
Year-over-year change is Motio’s principal measure of household-income direction and momentum. Real household-income growth had strengthened from 2.3% in March to 2.7% in April before easing to 2.6% in May. The full percentage-point decline in June sharply interrupted that stronger trajectory.
Although larger one-month declines in the real-income level occurred in May 2010 and January 2021, both took place during contractionary or pandemic-disrupted phases of the household-income series. June’s combination of a 0.5% decline in the level and a full percentage-point loss of year-over-year momentum represents the largest simultaneous weakening in the two measures recorded during an established expansion phase of the series.
“One month of weakness does not establish a turning point, and we would caution against interpreting it as one,” said Matías Scaglione, Co-Founder and Principal Economist at Motio Research. “June nevertheless warrants attention because both the level and momentum of real household income weakened substantially during an established upswing. Whether this reflects temporary volatility or the beginning of a broader deterioration in household-income conditions is the question the next several releases will help answer.”
Analyst's Notes
Political Calculations produces monthly median household income estimates using an alternate methodology that complements Motio Research's survey-based estimates. In June 2026, Political Calculations' initial estimate of median household income is $87,934. This estimate is $291 (or 0.3%) higher than our initial estimate of $87,643 for May 2026's median household income.
The following chart presents our estimates of U.S. median household income, both adjusted for inflation (blue) and not-adjusted for inflation (red) for each month from January 2000 through May 2026.
Political Calculations' June 2026 estimate is $176 (0.2%) below Motio Research's estimate of $88,110 for the month, which largely closes the gap we've observed between the two sets of estimates since Motio Research's estimates surged upward in July 2025.
For the latest in our coverage of median household income in the United States, follow this link!
References
U.S. Bureau of Economic Analysis. Table 2.6. Personal Income and Its Disposition, Monthly, Personal Income and Outlays, Not Seasonally Adjusted, Monthly, Middle of Month. Population. [Online Database (via Federal Reserve Economic Data)]. Last Updated: 30 July 2026. Accessed: 30 July 2026.
U.S. Bureau of Economic Analysis. Table 2.6. Personal Income and Its Disposition, Monthly, Personal Income and Outlays, Not Seasonally Adjusted, Monthly, Middle of Month. Compensation of Employees, Received: Wage and Salary Disbursements. [Online Database (via Federal Reserve Economic Data)]. Last Updated: 30 July 2026. Accessed: 30 July 2026.
Image credit: U.S. Census Bureau. We modified the public domain image to make it more generally applicable beyond reporting the median household income from 2022.
Labels: median household income
03 August 2026
The direction the S&P 500 (Index: SPX) takes is shaping up a lot like a playing a game that has a 50% chance of winning or a 50% chance of losing.
Investors saw that game play out during the past week as several of the Big Tech companies that dominate the index reported their earnings and updated their outlooks. For example, the world's biggest company, Apple (NASDAQ: AAPL) briefly touched a $5 trillion valuation before disappointing investors with its supply chain struggles, sending its shares lower.
But that loss was offset for the index as both Amazon (NASDAQ: AMZN) and Microsoft (NASDAQ: MSFT) were more positive.
By the time the trading week ended on Friday, 31 July 2026, the bulls came out ahead as the index rose almost 1.1% above its previous week's close to reach a value of 7,489.72.
The latest update of the alternative futures chart shows stock prices are consistent with investors focusing their forward looking attention on either the current quarter of 2026-Q3 or the more distant quarter of 2026-Q4.
The dividend futures-based model indicates very little difference in where it projects the level of the S&P 500 would be for investors fixing their attention on either these two future quarters.
As for why these two quarters would be of particular interest to investors, they happen to represent the likely timing of when the Fed will act to change the Federal Funds Rate. The CME Group's FedWatch Tool projects two quarter point rate hikes before the end of 2026. The first would occur after the Fed meets on 16 September (2026-Q3) and the second would take place on 9 December (2026-Q4).
Here are the market-moving headlines of the week that was:
- Monday, 27 July 2026
-
- Signs and portents for the U.S. economy:
- US core capital goods orders rise, shipments post largest gain in 4-1/2 years amid AI investment boom
- Oil prices settle at lowest in over a week, as US pauses attacks on Iran
- Bigger trouble, stimulus developing in China:
- China's industrial profit growth moderates as exports cushion uneven recovery
- China begins making homegrown DUV chipmaking tools, The Information reports
- China accuses US of 'AI hegemonism', threatens countermeasures over potential probes
- China opposes US 'forced labour' tariffs, calls for them to be cancelled
- BOJ minions getting excited to hike Japan's interest rates some more:
- ECB minions say interest rate hikes will continue until Eurozone morale improves:
- ECB's Kazimir: September rate hike likely needed even if outlook improves
- ECB facing mid-sized inflation shock, will get to 2% in year or so, Lane says
- Wall Street closed mixed as eyes remained focused on U.S.-Iran relations
- Tuesday, 28 July 2026
-
- Signs and portents for the U.S. economy:
- US goods trade deficit shrinks, is still expected to weigh on Q2 GDP growth
- Oil prices fall 5% to two-week low after several days without US-Iran strikes
- Fed minions not expected to hike U.S. interest rates this week:
- Uneven economic growth developing in China:
- Bigger trouble developing everywhere:
- S&P 500 ends higher as investors await tech earnings
- Wednesday, 29 July 2026
-
- Signs and portents for the U.S. economy:
- US mortgage rates climb again in latest week, many at year high
- Oil jumps 7% on escalating Middle East airstrikes
- OpenAI's rogue agent compromised a customer at a second tech firm
- Fed minions follow through on expectations with no rate hike, three minions dissented:
- Fed leaves rates unchanged; three policymakers dissent in favor of a hike
- VIEW Fed holds rates steady as three policymakers dissent for a hike
- No Rate-Change Sparks 3 Dissents As Warsh Fed Delivers Biggest 'Non-Cut' Surprise In Decades
- Fed meeting recap: Warsh says Fed won’t hesitate to stop inflation, but bond market has doubts
- Bigger stimulus developing in China:
- Wall Street ends lower as FOMC holds interest rates steady
- Thursday, 30 July 2026
-
- Signs and portents for the U.S. economy:
- US economic growth slows but domestic demand robust
- Oil edges down in choppy trading amid Oman-Iran talks, US-Iran tensions
- Fed minions see long-term interest rates rise after sending "muddled" message:
- Bigger trouble, smaller stimulus developing in China:
- China's factory activity expected to have stalled in July: Reuters poll
- China's leaders pledge to support economy without big new stimulus plans
- BOJ minions suspected of taking action to prop up Japan's currency:
- Faster growth, bigger inflation developing in Eurozone:
- Euro zone economy grows faster than expected on AI spending, confident consumers
- German inflation accelerates to 2.8% in July
- Wall Street closed higher as chips rallied and latest GDP and inflation figures landed
- Friday, 31 July 2026
-
- Signs and portents for the U.S. economy:
- Big Tech AI spending spree tops $1tn
- Anthropic's Claude AI hacked three companies during tests
- Oil falls more than $1 on greater flows despite US-Iran war
- US Treasury yield curve 'twist' reflects view Fed may not hike again
- Fed minions make case for September rate hike, some argue inflation is lowest it's been in years, chief Fed minion thinking about changing the schedule:
- Fed dissenters sketch the case for a rate hike
- As Warsh’s Fed faces pressure to act on inflation, these indicators show it’s at its lowest in years
- Warsh raised changing frequency of Fed policy meetings, NYT reports
- Bigger trouble, stimulus developing in China:
- China's factory activity shrinks in July as demand falters, fuelling slowdown concerns
- China approves eight new nuclear power units
- BOJ minions pass on hiking Japan's interest rates, but hint they'll resume hiking them later with inflation rising; also busy with propping up Japan's currency:
- Yen remains under pressure after BOJ kept rates unchanged
- Annual core inflation in Japan's capital accelerates in July
- BOJ nods to chance of early rate hike as Tokyo props up yen
- Japan intervenes to prop up yen ahead of BOJ policy decision, source says
- ECB minions see higher inflation in Eurozone:
- S&P 500 posts weekly gain as consumer discretionary shines
The BEA's first estimate of annualized real GDP growth during 2026-Q2 is 1.5%, just a bit below the Atlanta Fed's GDPNow tool's final estimate of +1.7% for the quarter. Meanwhile, GDPNow tool's first estimate of real GDP growth for the U.S. economy in the now current quarter of 2026-Q3 is +5.0%.
Image credit: Microsoft Copilot Designer. Prompt: "An editorial cartoon showing a Wall Street bull and bear spinning a Price Is Right style Big Wheel labeled 'WHICH WAY WILL STOCKS GO?’ with values 'UP' and 'DOWN'".
About Political Calculations
Welcome to the blogosphere's toolchest! Here, unlike other blogs dedicated to analyzing current events, we create easy-to-use, simple tools to do the math related to them so you can get in on the action too! If you would like to learn more about these tools, or if you would like to contribute ideas to develop for this blog, please e-mail us at:
ironman at politicalcalculations
Thanks in advance!
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